Total 1,350 job vacancies in Singapore

Location ; Kim Keat Road

Job Title: Assistant Manager / Manager / Senior Manager, Organisational Transformation (Policy)

Contract (1 year, with option to extend for another year subject to performance and conduct)

Working Hours:

• Monday to Thursday: 8.30am – 6.00pm
• Friday: 8.30am – 5.30pm
• 5-day work week (office-based)

Job Description:

• You will research, benchmark, and draft policy papers on organisational transformation.
• You will engage internal stakeholders to gather views and surface issues, and support consultations on transformation-related matters.
• Working across multiple workstreams, you will help align policy intent with implementation and communications, and provide secretariat support where needed.
• You will also monitor implementation progress and emerging issues, and help prepare updates for senior management.

Requirements:

• A degree in any discipline, with experience in policy development or the implementation of organisational initiatives
• Comfortable working with data to surface insights and support evidence-based recommendations
• Strong writing and communication skills
• Ability to work collaboratively across teams
  
  If you meet the requirements, please submit your resume directly to eg@businessedge.com.sg
• EA License No: 96C4864 Reg. No.: R1106922 Goh Khar Keow

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Engineer-%28SHINE-Programme-Management-and-Operations%29/33488-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

SHINE Programme Management and Operations 
•             Support the coordination and execution of SHINE research programmes in close collaboration with the Programme Director, principal investigators, researchers, and stakeholders.
•             Monitor programme deliverables, milestones, KPIs, and reporting timelines across SHINE projects and research thrusts.
•             Support coordination across SHINE research thrusts and facilitate interactions among principal investigators, researchers, industry partners, and funding stakeholders.
•             Coordinate and consolidate programme reports, including mid-term reviews, annual reports, final reports, presentations, and programme updates.
•             Support budget monitoring, grant utilisation tracking, expenditure reporting, fund requisitions, and budget virement processes.
•             Coordinate Governing Board (GB), Scientific and Technical Advisory Committee (STAC), programme review meetings, and related stakeholder engagements.
•             Assist in the preparation of technical and programme review materials, presentations, and supporting documentation.
•             Liaise with principal investigators, researchers, industry partners, and funding agencies to support programme execution and ensure timely delivery of project objectives.
•             Coordinate technical visits, industry engagements, and programme-related activities to support alignment between research activities and industry needs.
•             Maintain programme documentation, fixed asset records, compliance materials, and operational records.
•             Provide operational and administrative support for SHINE programme activities and initiatives as assigned.

Qualifications

 •            Possess a Bachelor's degree in a STEM discipline (Science, Technology, Engineering or Mathematics), preferably in Electrical Engineering, Computer Engineering, Materials Science, Physics, Mechanical Engineering, or a related field.
•             Relevant experience in research programme management, project coordination, industry collaborations, technology development programmes, research administration, or related functions would be advantageous.
•             Experience coordinating research projects, collaborative programmes, technical workshops, industry engagements, or multi-stakeholder initiatives.
•             Ability to engage effectively with principal investigators, researchers, students, industry partners, government agencies, and other stakeholders.
•             Strong interpersonal, communication, stakeholder management, and organisational skills.
•             Strong analytical and problem-solving abilities, with the capacity to manage multiple priorities and workstreams concurrently.
•             Familiarity with semiconductor technologies, advanced packaging, microelectronics, photonics, or related technology domains would be advantageous.
•             Experience in a university, research institute, government agency, corporate laboratory, or technology-related environment would be advantageous.
•             Proficient in Microsoft Office applications and comfortable working with project management and administrative systems.
•             Self-motivated, resourceful, and able to work independently in a dynamic research environment.
•             A collaborative team player with a positive attitude and strong attention to detail.
•             Open to appointment on a fixed-term contract

Job Description

ISCE2 isseeking a talented Research Engineer to be part of a young, dynamic, multi-disciplinary team to develop next-generation sustainable technology for the biomanufacturing of fine and specialty chemicals. This position offers an opportunity to develop new enzymes for streamlined manufacturing of complex molecules. The ideal candidate is passionate about science and sustainability, self-motivated, organised, detail-oriented, enjoys laboratory work, and has excellent communication and teamwork skills. The successful candidate may be responsible for but not limited to:

• Conduct experiments related to molecular biology, including molecular design and cloning
• Perform protein expression in bacterial systems, including molecular cloning, fermentation in bioreactors/shake flasks, and protein separation and immunoassays
• Design, plan, and execute experiments based on proposed project scope
• Be comfortable with the use of technology (i.e. automation and computation) to aid experiments
• Support screening, biocatalysts characterization, and hits validation efforts
• Analyze data, interpret results, and troubleshoot
• Presentation at regular project meetings and summarizing results in reports
• Presentation and review of relevant literature
• Assist in the preparation of scientific communications; publications, figures, and posters
• Perform general lab housekeeping
• Other duties as assigned by the manager

Requirements

• BSc or Master’s degree with some laboratory experience, preferably in Microbiology, Biotechnology, Chemical Engineering, or Biological Engineering.
• Preferred hands-on experience with microbial culture.
• Experience with bioreactors will be advantageous.
• Preferred hands-on experience with molecular cloning and bioanalytical techniques, such as PCR, Gel electrophoresis, LC-MS, etc.
• Team player who is self-motivated and enjoy applied research work in a multidisciplinary environment
• Adaptable to team-oriented goals and requirements
• Good problem-solving skills
• Rigorous data analysis and interpretation skills

Energy Research Institute @ NTU (ERI@N), established in 2010, has exceled in developing and delivering research relevant to industries. The institute integrates research across different schools within NTU to address energy challenge and subsequent translate into industrial scale and practices.

SCARCE (Singapore CEA Alliance for Research in Circular Economy) - a joint collaboration between NTU (Singapore) and CEA (France) – under ERI@N focus on recycling of electronic waste. One of the research thrusts is recycling of silicon solar panels and recovery of embedded materials – focusing in developing effective and efficient recycling pathway for the growing silicon solar panel waste

Energy Research Institute @NTU invites applications for the position of Project Officer to work on recycling of silicon solar panels. The role will focus on the hydrometallurgical processing of metals and silicon, including their dissolution and recovery, as well as supporting process scale-up activities

Key Responsibilities:

• Conduct comprehensive literature reviews and provide periodic updates on developments of hydrometallurgical approaches for recycling solar panel waste

• Perform and optimize hydrometallurgical processing of solar grey mass at both laboratory-scale and large-scale, along with electrorecovery of valuable materials

• Analyse metallic concentrations in leachate solution and conduct material characterisation on residues or solar grey mass (e.g. ICP-OES, SEM/EDX, particle size analyzer)

• Participate in collaborative work with team members and external collaborators, including preparation of technical reports, videos, manuals and presentation of results

• Assist with laboratory logistics, administrative tasks, and coordination of project-related activities to ensure smooth operations

Job Requirements:

• Bachelor in chemistry/chemical engineering/material science or related fields is required.

• Familiarity with material characterization techniques such as SEM-EDX, XRD, ICP-OES would be advantageous.

• Hands-on experience in electrochemical analysis techniques would be advantageous.

• Entry level candidates are welcome to apply

• Willingness to learn, with adaptability and flexibility to take on tasks beyond the job description

• Strong communication and interpersonal skills and ability to work cohesively in a team whilst sharing resources

We regret to inform that only shortlisted candidates will be notified.

At Meta, we’re building the future of human connection and the technology that enables it. This means continuously inventing and developing technologies for the next generation of experiences. To continue our efforts in the path to AGI, and as we move closer to a future with intelligent robots and advanced AI models, we're hiring talent across a broad range of disciplines from robotics hardware to system software and artificial intelligence. These crucial projects and initiatives taken on by this team have never been done before, so you have a rare opportunity to help us create new ways people connect around the world.

We’re seeking Research Scientists ready to use their skills in system design and modeling and with a knowledge of a wide variety of components and technologies. These roles will require research and problem-solving skills, as well as fabrication and prototyping to design, develop, and construct novel prototypes and architectures. These roles will work in a focused incubation team and collaborate with a large and wide-ranging set of scientists and engineers in the greater organization.

Responsibilities

• Perform fundamental and applied research to push the scientific and technological frontiers of embodied artificial intelligence
• Invent/improve novel data-driven paradigms for robotics, leveraging a variety of modalities (images, video, text, audio, tactile, etc)
• Investigate paradigms that can deliver a spectrum of embodied behaviors - from simulated characters to real robots, and from short-horizon, low-level to long-horizon, high-level intelligence
• Develop algorithms based on state-of-the-art machine learning and neural network methodologies
• Define, build and benchmark new functionalities needed for the next generation of AI
• Conduct research towards long-term product goals while identifying intermediate milestones
• Lead, plan, and execute novel research based on long-term objectives of the organization

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Experience with any of the following research areas: robotics, motion planning, embodied AI, human-robot interaction, sim-to-real transfer, learning from demonstration, reinforcement learning, dexterous manipulation, digital agents, vision language models, computer vision, egocentric perception, and/or LLMs

Preferred Qualifications

• Experience solving complex problems and comparing alternative solutions, trade offs, and varied points of view to determine a path forward
• Demonstrated experience in building large scale recommendation systems
• Experience working and communicating cross-functionally in a team environment
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as RecSys, CVPR, ICCV/ECCV, ICLR, ICML or NEURIPS

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

The School of Physical and Mathematical Sciences is a center for a broad spectrum of mathematics, pure and applied. 

There is an opening for a research fellow in the group of Dr. Milind Hegde. The research will broadly be in the area of stochastic growth models and the Kardar-Parisi-Zhang universality class, though related areas of probability may also be of interest.

The position is for a maximum of 3 years. It does not come with any teaching obligations, though there may be opportunities for those interested in some light teaching for the purpose of career development. There will be adequate funds available for academic travel.

Key Responsibilities:

• Perform research into KPZ

• Potentially aid in organization of research events focused on probability theory and KPZ 
  

Job Requirements:

• A PhD with a focus in probability theory or a closely related area.

• Strong research record

• Preferred but not required: Research experience in KPZ, interacting particle systems, integrable probability, first or last passage percolation, polymer models, or random matrix theory
  

We regret to inform that only shortlisted candidates will be notified.

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Assistant-%28Physics%29/33339-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The successful candidate will work with Associate Professor Utkur Mirsaidov on exciting research nanoscience projects using cutting-edge in-situ high-resolution transmission electron microscopic techniques (TEM).

Main responsibilities:

• Responsible for micro- and nanofabrication, process improvements, and developing designs for new devices.
• Since the candidate will be working in an international and multicultural environment, fluency in English and good people skills are essential.
• We are a group of dynamic and creative researchers who love science, looking for like-minded candidates who are willing to head on challenges and go extra miles.

The successful candidate is also privileged to be trained on advanced microscopic techniques that bring you to the next level in the research world.

Training provided:

• Transmission electron microscope (TEM)
• Scanning electron microscope-focus ion beam (SEM-FIB)
• 2D material transfer and fabrication

Qualifications

Bachelor Degree or higher in one of the following disciplines: Physics, Engineering, Mathematics.

Skills:
•    Main: Solid programming skills with experience in Python/Matlab/
•    Bonus: Imaging process, visualization, scientific image analysis experience, cleanroom (microfabrication) experience.
•    Possess great interpersonal and communication skills, hard-working, and not afraid of challenges

The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE prides itself in its excellent research capabilities in areas including advanced manufacturing, aerospace, biomedical, energy, industrial engineering, maritime engineering, robotics, etc. The school is equipped with state-of-the-art research infrastructure, housing a comprehensive range of cluster laboratories, test bedding facilities, research centres/institutes and corporate laboratories. Cutting-edge research in MAE addresses the immediate needs of our industries and supports the nation’s long-term development strategies. In the new era of industrial 4.0 and sustainable living, MAE is rigorous in developing new competencies to support the growth and competitiveness of our engineering sector in the global landscape. MAE has grown to be leader in Engineering Research, ranking amongst the top engineering schools in the world.

For more details, please view https://www.ntu.edu.sg/mae/research.

The School of Mechanical and Aerospace Engineering (MAE) is seeking to hire a Research Fellow

• To design and advance the Centre’s research activities in biomedical optics–related projects.

• To conduct research in experimental optics for diagnostics and spectroscopy by developing novel approaches for bioimaging experiments and instrumentation. The position also offers opportunities to collaborate with external partners.

Key Responsibilities:

The RF will support focused research activities at COLE. He/ She will assist the Principal Investigators (PIs) in the successful execution of the projects and will also be encouraged to introduce new ideas and projects. The roles of this position include:

• Design and conduct experiments for diagnostic and spectroscopic analysis of biological samples.

• Prepare and handle biological samples, including cells, tissues, organoids, or in vivo models, in accordance with biosafety and ethical protocols.

• Manage the research project in a team-based, cross-functional research environment, which includes mentoring students and working collaborators, technical and other support staff.

• Publish research outcomes in journals of international standing; Attend and present research findings and papers at academic meetings and contribute to the external visibility of the Centre.

• Draft research reports for PIs and undertake specific roles and management functions as may be reasonably required by the PIs.

• Assist in drafting project proposals.

• Attend meetings and participate (where necessary) in other committees and working groups.

• Ensure compliance with health and safety in all aspects of the research work.

• The research staff is expected to work with the PI and other team members for doing R&D and take key role for the development of the systems for bioimaging and metrology

• Conduct and coordinate research within NTU and collaborating partners in line with its research strategy under the supervision of the PIs and collaborators

• Publish research outcomes in journals of international standing; Attend and present research findings and papers at academic meetings, and contribute to the external visibility of the centre.

• Draft research reports for PIs and undertake specific roles and management functions as may be reasonably required by the PIs.

Requirements:

• PhD in Optical Engineering, Mechanical Engineering, Precision Engineering, Electronics Engineering, Physics or a similar discipline with optics, spectroscopy and instrumentation background

• Previous Hands‑on experience with optical diagnostics, spectroscopy, or imaging techniques is highly desirable.

• Expertise in the handling of human biological samples and translational biomedical research.

• Possess good programming and automation skills (e.g. C++, MATLAB, Python, LabVIEW)

• Proven publication track record would be an advantage

• Expertise in optical instrumentation would be an advantage (e.g. Zemax, TracePro, Virtual Lab, OSLO, MATLAB, Python, ImageJ)

• Strong written and spoken communication skills

• Proven publication track record would be an advantage

We regret to inform that only shortlisted candidates will be notified.

Project Overview

This project aims to develop a real-time blood analysis and diagnostic platform using an integrated microfluidic chip. This platform uses precision microfluidic technology to process and profile the biological activity of white blood cells which is related to a host of inflammatory conditions ranging from diabetes, sepsis to leukemia. The platform developed will enable point-of-care diagnosis of diseases and this project will accelerate the platform from bench to bedside through the development, deployment and testing of clinical samples.

This Engineering position offers a rare opportunity to bridge the gap between laboratory discovery of new technologies and real-world implementation of clinical deployment and testing. 

Responsibilities

The engineer is responsible for the design, prototype, manufacturing and testing of the medical device. This involves the use of with computer-aided design prototyping, setting specifications and assembly of mechnical/electrical components, testing and deployment of device for field testing.

Responsibilties include:

- To work closely with a team of clinical, mechanical/software engineers and data scientist for the medical device design and prototyping. Gather feedbacks on prototype designs by end-users.

- To Validate designs by analysing data gathered from component or system level testing. Use benchmarking techniques to characterise component and device performance.

- To ensure proper documentation of design history files and standardization of data storage for reports, presentations, technical and administrative documents.

- To source for vendors and components to ensure manufacturability and cost of medical device.

- To support the team for maintenance of equipment, inventory and purchases.

Requirements

- Bachelors/Masters in Mechanical, Electrical, Biomedical Engineering with at least 1 years of experience in hardware prototyping and/or microfluidic operations.

- Rapid prototyping experience in areas such as 3D printing, laser cutting, CNC, injection molding, microcontroller/microprocessor programming and relevant skills in embedded system.

- Prefered experience in commercial manufacturing, R&D project management and hardware testing/certification.

- Excellent debugging skills and strong ability to root cause, isolate and solve software/hardware system issues.

- Fluent in C++, Python (3.X) and relavent coding languages for software-hardware integration.

- A desire to deliver a quality and innovative medical diagnostic product that improves many people’s lives.

- Good communication and managing skills are important to work with colleagues efficiently in addition to creativity to solve problems and find improvements on products and processes already in place.

- Required experience and knowlegde to read or write scientific publications, patent search, schematics and data sheets for hardware components.

- Able and commited to work in Singapore. Willing to commute and meet regularly with vendors and collaborators at NUS, NUH, and partnering hospitals.

- Strong documentation and writing skills

- A desire to deliver a quality and innovative medical diagnostic product that improves many people’s lives.

Relevant Skills

2D/3D Computer Aided Designs, C++, Python, Operating CNC/3D printers, basic use of machine tools, electronics circuit design, Github 

To apply, please visit our website at: https://portal.smart.mit.edu/careers/career-opportunities

Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.

COMPANY DESCRIPTION

Singapore Management University is a place where high-level professionalism blends together with a healthy informality. The 'family-like' atmosphere among the SMU community fosters a culture where employees work, plan, organise and play together - building a strong collegiality and morale within the university.

Our commitment to attract and retain talent is ongoing. We offer attractive benefits and welfare, competitive compensation packages, and generous professional development opportunities - all to meet the work-life needs of our staff. No wonder, then, that SMU continues to be given numerous awards and recognition for its human resource excellence.

RESPONSIBILITIES

• This position is for School of Computing and Information Systems (SCIS).
• Data preparation, processing, analysis and annotation.
• Development of deep learning and AI-based methods.
• Report writing.
• Statistical analysis.
• Meeting arrangement.
• Presentation.
• Other duties assigned

• Minimum PhD degree in Computer Science, Information Technology, Information Systems or closely related disciplines with particular focus on deep learning and AI.
• Minimum 2 years of relevant research experience in deep learning and AL.
• Some knowledge in machine learning, data analysis and statistics.
• Programming in Python will be an advantage.
• Knowledge in large language model prompting.
• Experience with research works is preferred.
• Good analysis and problem-solving skills.
• Applicants with research publications in related areas will be advantageous.
• Self-motivated individual who can work independently and with team members.

#LI-JN2

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Wireless-Optical-Communication-Optical-Memory%29/33481-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Work on hands-on experiments for few of the following tasks:
1. Design, Simulation, and Fabrication of MEMS and Photonics 
2. Design, modelling and testing of Si Photonics
3. Design and set-up testing for high-speed microwave photonics
4. Experience in using the RX6000 and NVidia CUDA toolkit
5.Write 2 or more research papers based on derived data of the above devices in the first year in the top-notch journals
6. Write research grant proposals
7.Supporting and guiding the experiments of MSc students

Qualifications

1. Have learned MEMS, Photonics and high-speed microwave communication system related courses for one semester at post-graduate level and earned score of A- or better.
2. Strong background in hands-on microfabrication techniques at clean room and with journal publications showing such evidences
3. With 1 year and more experience in MEMS design , making and testing MEMS/Photonics
4. Strong knowledge in L-Edit; Lumerical; CST; COMSOL; ANSYS; 
5. Fluent in English speaking and writing
6. Having more than 1 1st-authored international peer-reviewed journal papers, e.g., Nature Communications and Science Advances (for Research Engineer)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Microbiology-&-Immunology%29/22121-en_GB/?st=8D4EEF9B0E1A95200D1286536EB80500394C0095

We regret that only shortlisted candidates will be notified.

Job Description

The National University of Singapore invites applications for Research Assistant for “Singapore Integrated Network for Genomic and Epidemiological Tick-borne Pathogen Investigation and Connectivity” in the Department of Microbiology & Immunology, Yong Loo Lin School of Medicine. The Department of Microbiology and Immunology (https://medicine.nus.edu.sg/mbio/) at NUS is dedicated to advancing research, teaching, and training in infectious diseases, immunity, and host-pathogen interactions. It is well known for strengths in immunology, virology, bacteriology, parasitology, and molecular biotechnology, supported by strong core research facilities and graduate training opportunities. Appointments will be made on a 1-year contract basis in the first instance, with the possibility of extension.

Purpose of the post

The Research Fellow (RF) will work closely with the Principal Investigator (PI) and study team to ensure timely, high-quality delivery of a tick and tick-borne disease biosurveillance project in Singapore. The RF will support end-to-end study operations, including coordination with study sites, participant/sample workflows, data management, analysis, and reporting, while maintaining strong professional standards and accurate documentation.

Main duties and responsibilities

The RF will liaise with relevant personnel across study sites (e.g., clinics/hospitals and partner units) to support smooth recruitment and data/sample collection processes and will be accountable to the PI. The RF will be able to:

1. Oversee the general management of the project, including planning, coordination and day-to-day troubleshooting to ensure milestones are met;
2. Provide administrative and secretarial support to the project, such as organizing regular meetings to maintain regular communication with other members of the research team and collaborate with the study sites;
3. Undertake the day to day running of the project at the study site, e.g. collaborate with team members at the study sites, support recruitment, coordinate field/site activities, and support data and/or sample collection at sites and relevant settings;
4. Conduct literature searches, support maintenance of the study database, perform data entry and cleaning, and analyse data using appropriate software tools; as well as assist in preparing both progress and final reports of the project;
5. Apply bioinformatics and AI-enabled approaches to support genomics and proteomics-related analyses as required by the study (e.g. use relevant bioinformatics tools and machine learning/deep learning workflows to support interpretation and reporting);
6. Maintain the highest standard of professional conduct and record keeping in accordance with policies and procedures, including accurate documentation and data integrity.

Qualifications

The applicant should:

1. Have a first degree with good results or holds a PhD degree in Biotechnology, Microbiology, Biochemistry, Molecular Biology;
2. Have a background in infectious pathogens and infection-related research, with training/exposure in microbiology, immunology and/or clinical microbiology, and experience working with pathogen-focused research questions;
3. Be able to work independently and in a team, have an investigative nature and attention to detail, and be able to deliver reports and presentations to stakeholders;
4. Have knowledge of computer applications and research software for data handling, analysis and reporting (e.g. MS Office/PowerPoint, EndNote/Mendeley, GraphPad Prism) and be familiar with computational/bioinformatics tools and workflows (e.g. machine learning approaches and sequence-based tools such as BLAST);
5. Have experiences in relevant areas of research spanning wet-lab and computational work, such as microbiology/molecular biology methods (e.g. biofilms, RNA extraction, RT-qPCR, ELISA, mammalian cell culture) and computational/AI methods (e.g. virtual screening/docking, molecular dynamics simulations, and machine learning model development).

Remuneration will be commensurate with the candidate’s qualifications and experience. Informal enquiries are welcome and should be made to Dr Benoit Malleret at benoit_malleret@nus.edu.sg.

Formal application: Please submit your application, indicating current/expected salary, supported by a detailed CV (including personal particulars, academic and employment history, complete list of publications/oral presentations and full contacts of three (3) referees to the NUS Career Portal.

We regret that only shortlisted candidates will be notified.

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Assistant-%28Microbiology-&-Immunology%29/20750-en_GB/?st=BBE292BB043DB988997818261DB218F6EFE0D99F

We regret that only shortlisted candidates will be notified.

Job Description

The National University of Singapore invites applications for Research Assistant for “Singapore Integrated Network for Genomic and Epidemiological Tick-borne Pathogen Investigation and Connectivity” in the Department of Microbiology & Immunology, Yong Loo Lin School of Medicine. The Department of Microbiology and Immunology (https://medicine.nus.edu.sg/mbio/) at NUS is dedicated to advancing research, teaching, and training in infectious diseases, immunity, and host-pathogen interactions. It is well known for strengths in immunology, virology, bacteriology, parasitology, and molecular biotechnology, supported by strong core research facilities and graduate training opportunities. Appointments will be made on a 1-year contract basis in the first instance, with the possibility of extension.

Purpose of the post

The Research Assistant (RA) will work closely with the Principal Investigator (PI) and study team members to support the successful completion of a tick and tick-borne diseases biosurveillance project in Singapore. The RA’s principal role will be to support field sampling and surveillance activities, manage and process study data for analysis and reporting, and contribute to accurate record-keeping and documentation to ensure project milestones are met on time.

Main duties and responsibilities

1. The Research Assistant will liaise with relevant personnel to facilitate the smooth running of fieldwork and related data workflows and will be accountable to the Principal Investigator (PI). The RA will be able to:
2. Provide administrative support to the project, such as organising regular meetings, maintaining communication with research team members and collaborators, and supporting scheduling and tracking of project tasks.
3. Support the day-to-day coordination of project activities, including planning and logistics for biosurveillance fieldwork across multiple sites in Singapore.
4. Provide administrative support to the project, such as organising regular meetings, maintaining communication with research team members and collaborators, and supporting scheduling and tracking of project tasks.
5. Assist with fieldwork operations at study sites, including supporting systematic collection activities and maintaining clear, consistent field records in line with project protocols.
6. Manage, clean, and process field and project data for analysis and reporting, maintaining well-organised datasets and contributing to the upkeep of project databases.
7. Support basic data analysis, visualisation, and reporting using relevant tools (e.g., MS Office, R Studio; ArcGIS where spatial outputs are needed), and assist with preparing progress updates and final reports.
8. Maintain high standards of professional conduct, data integrity, and record-keeping in accordance with project policies and procedures.
9. Assist with any other duties of a similar nature as delegated by the PI.

Qualifications

The applicant should:

1. Demonstrate competence in GIS-based mapping and spatial analysis (e.g., using ArcGIS), with the ability to support vector and tick-borne disease biosurveillance mapping and the integration of environmental and climate-related spatial data (e.g., satellite-derived indices, land cover, and other relevant layers) for analysis and reporting.
2. Have experience with field-based sampling and surveys, including working across varied habitats and maintaining accurate field notes, metadata, and sample documentation in accordance with project protocols.
3. Have a background in species identification and specimen handling, including experience with morphological documentation and/or contributing to species or ecological databases, with strong attention to detail in recording and data quality.
4. Have familiarity with molecular biology laboratory workflows relevant to biosurveillance (e.g., DNA extraction and PCR), and be able to follow laboratory protocols, maintain clear lab records, and support downstream identification workflows as required.
5. Be comfortable managing and organising datasets for analysis and reporting, and be proficient with standard productivity and data tools (e.g., MS Office), with added advantage of experience in analytical software (e.g., R).
6. Be able to work independently and collaboratively, with strong organisational and communication skills, and a professional approach to safety, confidentiality, and research integrity.

Remuneration will be commensurate with the candidate’s qualifications and experience. Informal enquiries are welcome and should be made to Dr Benoit Malleret at benoit_malleret@nus.edu.sg.

Formal application: Please submit your application, indicating current/expected salary, supported by a detailed CV (including personal particulars, academic and employment history, complete list of publications/oral presentations and full contacts of three (3) referees to the NUS Career Portal.

We regret that only shortlisted candidates will be notified.

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Global-Research-Partnerships-Consultant-%28Part-Time%29/33472-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

About the Centre

The Centre for Biomedical Ethics (CBmE), Yong Loo Lin School of Medicine, National University of Singapore, is a leading centre for teaching, research and engagement in biomedical ethics, health law, clinical ethics, research ethics, public health ethics, AI ethics, neuroethics and related fields.

CBmE is responsible for the development and delivery of the Health Ethics, Law and Professionalism programme across the undergraduate medical curriculum, and also contributes to postgraduate and continuing professional education in bioethics. The Centre works closely with academic, clinical, policy, regulatory and professional stakeholders in Singapore and internationally.

As CBmE continues to grow its international research profile, regional partnerships and global engagement, the Centre seeks to appoint a part-time International Research Partnerships Consultant to provide specialist support for international research collaboration, strategic academic partnerships, grant development and outward-facing academic engagement.

About the role

The Part-Time Consultant will support the Centre’s international collaborations, strategic partnerships and outreach beyond Singapore. The role is intended to strengthen CBmE’s international profile and research development capacity by supporting the identification and development of international collaborations, research networks, funding opportunities and strategic initiatives. It is a part-time, advisory and project-based role.

The appointment will be offered on a part-time consultancy basis for up to 25 hours per week, subject to agreed deliverables.

Responsibilities of the role as below:

• Support the Head of CBmE in international engagement strategy, including priority regions, institutions, networks and partnership opportunities aligned with the Centre’s mission in biomedical ethics, health policy, research ethics, clinical ethics, neuroethics, AI ethics and related areas.
• Identify and assist with large international grant opportunities
• Identify, maintain or facilitate philanthropic support opportunities, including working with the Development Office of YLLSOM
• Work with CBmE academic and leadership teams to identify areas where international collaboration can strengthen research impact, policy engagement, education, public engagement and capacity building.
• Provide academic development support for international initiatives, including scoping new partnership models, shaping value propositions, preparing concept notes, and advising on pathways for collaborative programmes, networks, funding opportunities and thought leadership activities, including identifying new income stream opportunities.
• Support CBmE’s international positioning by identifying emerging trends and opportunities, and advising on how CBmE can contribute to international debates and collaborations.
• Support the development of outward-facing international materials, including partnership briefs, strategic narratives, concept papers, talking points and presentations for external stakeholders.
• Help track and review the progress of selected international engagement opportunities, including key contacts, next steps, strategic value and possible follow-up actions for CBmE leadership.
• Assist the Head in international engagement, impact, and research as required.
• Undertake other strategic liaison, advisory and partnership development duties as agreed with Head of CBmE, within the scope of the consultancy.

Qualifications

ESSENTIAL CRITERIA

Applicants should have:

• A good degree, in a field relevant to bioethics.
• Significant experience in research management in an international context, research facilitation, academic centre administration and strategic research support within the University sector.
• Experience supporting academic collaborations involving more than one institution, country or region.
• Experience with grant development, funding applications, research budgets, funder liaison, grant reporting or research portfolio coordination.
• Experience preparing reports, briefings or materials for donors, philanthropic partners, funders or senior institutional stakeholders.
• Strong understanding of how academic research centres operate, including the relationship between research, grants, partnerships, institutional processes and external engagement.
• Excellent written and oral communication skills, including experience preparing high-quality materials for academic, institutional, funder, donor, policy or senior stakeholder audiences.
• Strong organisational skills, sound judgment, discretion and professionalism.
• Ability to work independently in a part-time advisory role while collaborating constructively with academic, administrative and leadership colleagues.

DESIRABLE CRITERIA

• Experience working in or with a leading research-intensive university or internationally recognised academic institute.
• Experience in working with biomedical ethics, practical ethics, health policy, clinical ethics, research ethics, AI ethics, neuroethics, public health ethics or a related area.
• Experience supporting the development or growth of a research centre, academic programme, research network or strategic initiative.
• Experience supporting substantial externally funded research portfolios.
• Experience working across time zones, institutional systems and cultural contexts.

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28National-Centre-for-Engineering-Biology%29/33480-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are seeking one highly motivated and creative postdoctoral researcher to join our dynamic team at the Synthetic Biology for Clinical and Technological Innovation (SynCTI), Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore (NUS) and the National Centre for Engineering Biology (NCEB).  

The selected Research Fellow will work collaboratively with the Principal Investigator (PI) and our research team on projects aimed at advancing sustainable bioproduction. Appointments will be initially made on a 1-year contract, with the possibility of extension. PhD holders with no experience are welcome to apply.

Ideal candidates will possess expertise in metabolic pathway engineering, microbial engineering and the development of cell factories for bioproduction. We particularly encourage applicants with a background in metabolic engineering, genome editing and bioprocess development for biochemical production. The successful candidate will assume a pivotal role in advancing the frontier of synthetic biology to address real-world challenges.

Join us in shaping the future of innovative biotechnology and making significant progress towards sustainability and technological advancement!

Main Responsibilities:
The Research Fellow is expected to: 
1) Develop biological parts, genetic circuits, or tools for engineering microorganisms; 
2) Metabolically engineer microorganisms with high bioproduction capabilities for industrial applications in the production of value-added biochemicals;
3) Write papers together with the PI for publication in high-impact journals;
4) Mentor research assistants, graduate, and undergraduate students; 
5) Assist in any other duties delegated by the Principal Investigator and group leaders. 

Remuneration will be commensurate to the candidate's qualifications and experience. Informal enquiries are welcome and should be made to Ms Suhana Sulaiman, at suhana_s@nus.edu.sg.

Formal application: Please submit your application, indicating job reference number and current/expected salary, supported by a detailed CV (including personal particulars, academic and employment history, complete list of publications, oral presentations, and full contacts of 3 referees) to the NUS Career Portal. Only shortlisted candidates will be notified.

Qualifications

Job Requirements:
1) Hold a PhD in Biotechnology, Biological Sciences, Biochemistry, or related disciplines; 
2) Have extensive knowledge and hands-on experience on genetic parts assembly, pathway engineering, microbial strain engineering, fermentation, recovery and analytics of targeted metabolites; 
3) Have the ability to design and perform experiments for microbial strain engineering, gene expression, protein expression, enzymatic assays, microbial fermentation, and product recovery; 
4) Know how to work independently and in a team, have an investigative nature and a strong attention to detail;
5) Possess an established record of international publications

1. Period: 1 year contract

2. Location: Airport Road

3. Working Hours: Mon – Fri: 0800-1735

4. Salary: Up to $2200

Job Descriptions: 

• Account for all delivered tools and perform preliminary inspections to identify and report any discrepancies or damage

• Perform and assist in the maintenance of tools and equipment in strict accordance with manufacturer manuals and relevant safety regulations

• Proactively update, monitor, and arrange for scheduled inspections, calibrations, and load tests to ensure all tools meet due-date requirements

• Set up and maintain organized tool boards and toolboxes to ensure a safe, efficient, and orderly working environment

Job Requirements:

• Higher Nitec or Diploma in Engineering

• Ability to read and interpret basic technical manuals and engineering diagrams

• 1 year experience in engine maintenance preferred

If you are interested, please submit your application here. We appreciate your application and will notify you if you are shortlisted for the role.

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EA License No: 90C3494 | EA Personnel No: R21103663 | EA Personnel Name: Azhar Anuwar

The School of Civil and Environmental Engineering (CEE) at Nanyang Technological University is a leading school for Sustainable Built Environment. It has over 60 faculty members and more than 1,500 students and is rapidly expanding its range of education and research activities. We are looking for a Research Associate to conduct life-cycle assessment on solid waste treatment and management systems.

Key Responsibilities:

• Design and implement experimental studies on solid waste treatment processes, including rigorous data analysis and comprehensive technical evaluation.

• Integrate experimental findings with quantitative modeling and life-cycle assessment (LCA) to assess system performance and environmental impacts.

Job Requirements:

• Master’s degree in Geotechnical Engineering, Environmental Engineering or related field

• At least 1 year of relevant experiences in life-cycle assessment

• Familiarity with related literature and software

• Good written and oral communication skills

• Entry level candidates are welcome to apply

We regret to inform that only shortlisted candidates will be notified.

The School of Chemistry, Chemical Engineering and Biotechnology (CCEB) at NTU Singapore, in collaboration with Wageningen University & Research (WUR), is part of Singapore Indoor Farming System (SingFarm)—a CREATE-NRF programme focused on building a sustainable, data-driven food production model with strong industry relevance to contribute Singapore’s ambition in achieving 20 per cent local production of its fiber (vegetables, mushrooms etc.) by 2035. The candidate would be working in a multinational team at the forefront of Singapore’s agricultural innovation and food security.

The successful candidate will work in Work Package 3.3: Urban Demo Lab. In this role, you help translate research results from across the program into demonstrators and settings for collaborative exploration that allow key stakeholders to engage with emerging food production technologies – and each other. The Urban Demo Lab serves as a platform where researchers, industry partners, and other stakeholders explore applications, provide critical design feedback and identify opportunities for further innovation: it serves as an attractor for future projects and strategic alliances that maximize the urban impact of ongoing research and development.

As an innovation facilitator, your work provides the active interface that is needed between research, technology translation, and stakeholder engagement. By stimulating dialogue and collaborative learning, you identify critical friction zones and promising ways forward, effectively accelerating the uptake of scientific innovations in real-world applications.

Key Responsibilities:

• Collaborate with research teams to identify key elements of research suitable for demonstration.

• Facilitate workshops, meetings, and stakeholder sessions to explore research outcomes, gather feedback, and identify innovation opportunities.

• Translate scientific insights into demonstrators, prototypes, or other formats such as an overall performance dashboard that communicate application potential to diverse audiences.

• Contribute to identifying and engaging potential partners or funders interested in further development of promising ideas.

Job Requirements:

• Completed PhD in a relevant field (e.g., food systems, food production, sustainability transitions or related fields).

• Systems thinker with an interest in innovation in food production and controlled environment agriculture

• Experience translating scientific research into practical applications, demonstrators or stakeholder-facing outputs.

• Excellent communication skills and ability to work across disciplinary and organizational boundaries.

• Experience facilitating interdisciplinary collaboration, workshops, or stakeholder engagement is an advantage.

We seek a diverse and inclusive workforce and is committed to equality of opportunity. We welcome applications from all and recruit on the basis of merit, regardless of age, race, gender, religion, marital status and family responsibilities, or disability.

We regret that only shortlisted candidates will be notified.

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Senior-Research-Fellow-%28%C2%B9%E2%81%B7%E2%81%B6Lu%E2%81%BA-Optical-Clock-Laboratory%29/33440-en_GB/

We regret that only shortlisted candidates will be notified.

About the Centre for Quantum Technologies (CQT)

The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena. Experts in this new discipline of quantum technologies are applying their discoveries in computing, communications, and sensing.
CQT is hosted by the National University of Singapore. The Centre also has staff at the Agency for Science, Technology and Research, Nanyang Technological University, Singapore, and the Singapore University of Technology and Design. With some 200 staff and students, it offers a friendly and international work environment

Learn more about CQT at https://www.cqt.sg/

Job Description

The Barrett group at CQT is the world's leading laboratory developing ¹⁷⁶Lu⁺  as an optical clock species. Lutetium-176 offers exceptionally low sensitivity to blackbody radiation shifts and a highly favourable systematic
uncertainty budget, making it a compelling candidate for next-generation optical timekeeping. Our programme isactively pushing towards multi-ion clock architectures — including linear ion crystals and multiplexed trap arrays —to surpass the quantum projection noise limits of single-ion operation and achieve unprecedented clock stability atshort averaging times. A key aim of the programme is to translate this technology into a commercialisable turnkeysystem for deployment at Singapore's National Metrology Centre (NMC).

We are seeking an exceptional Senior Scientist to lead experimental research within our ¹⁷⁶Lu⁺ optical clockprogramme at the Centre for Quantum Technologies (CQT), Singapore. This is a senior individual-contributor
position at the cutting edge of precision quantum metrology, with direct impact on international timekeeping,tests of fundamental physics, and Singapore's national measurement infrastructure.The successful candidate will drive original research, take ownership of key experimental subsystems, mentor junior researchers and graduate students, engage with industry and national metrology partners, and contribute to the long-term scientific and translational roadmap of the laboratory.

Key Responsibilities

• Lead the design, development, and operation of ion trap systems for ¹⁷⁶Lu⁺, including the engineering of novel trap geometries suited to multi-ion clock operation..
• Drive the experimental realisation of multi-ion clock configurations: ion crystal preparation, laser cooling, and correlated interrogation schemes for stability beyond the standard quantum limit.
• Develop and maintain ultra-stable laser systems and optical frequency infrastructure, including cavity-stabilised clock lasers and optical frequency combs.
• Contribute to optical frequency comparison and dissemination capabilities, including fibre-link and satellite-based clock comparisons.
• Work closely with local industry and metrology partners to develop a commercialisable turnkey ¹⁷⁶Lu⁺ clock system suitable for implementation at the A*STAR National Metrology Centre (NMC).
• Mentor postdoctoral researchers and PhD students; contribute to grant applications, scientific reporting, and laboratory operations.

Required Qualifications

• PhD in Physics with specialisation in AMO physics, precision metrology, or quantum information science.
• Demonstrated track record of high-impact independent experimental research evidenced by peer-reviewed publications.
• Hands-on expertise in ion trapping: rf Paul traps, trap fabrication or characterisation, micromotion compensation, and laser cooling of atomic ions.
• Proficiency with ultra-stable laser systems: cavity-stabilised lasers, laser locking, optical frequency chains, and electro-optic/acousto-optic control.
• Strong experimental skills in ultra-high vacuum technology, optical design, and precision rf and digital electronics.
• Excellent written and oral communication skills with the ability to present complex results to both specialist and general audiences.

Preferred Experience

Cryogenic ion traps

Experience operating ion traps at 4 K or below, including pulse-tube or dilution refrigerator integrationand cryogenic rf delivery.

Multi-ion architectures

Ion crystal formation and control, mixed-species crystal operation, or multiplexed trap-array design and characterisation.

Optical frequency metrology

Optical frequency comb operation, absolute frequency measurement, or fibre-based optical clock comparison and dissemination.

Experimental automation

Python-based experiment control, FPGA or ARTIQ sequencing, and real-time digital feedback for clock servo loops.

Additional Information

What we offer:

• Competitive, commensurate with experience.
• Dedicated equipment & travel allowance.
• World-class research hub at the NUS campus in Singapore.

To apply, please submit a CV, a research statement describing your relevant expertise and vision for the Lu+ clock programme (max 2 pages), and the names of three referees. Applications are reviewed on a rolling basis — early submission is encouraged. Inquiries should be directed to Prof. Murray Barrett at phybmd@nus.edu.sg

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Assistant-%28Relative-smooth-optimization-theory%29/33396-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

In recent decades, we have witnessed significant progresses in the convergence and complexity theory of the first-order optimization methods, with gradient global Lipschitz continuity (GGLC) assumption playing a central role, in many classical results. However, a large class of important problems arising in modern optimization and machine learning do not satisfy this assumption. As a result, there remains a substantial gap between the theory and practical behavior of many widely used algorithms.

This project, led by Dr. Zhang, aims to strengthen the theoretical foundation of relative smooth optimization, an emerging framework developed to go beyond the classical GGLC setting. In particular, the project will study first-order methods under relative smoothness, with a focus on nonconvex problems, more appropriate optimality measures, and new non-Euclidean Lipschitz tools that better capture the underlying problem geometry. The goal is to establish sharper convergence and complexity results, clarify several widely adopted but potentially misleading arguments in the current literature, and develop a more reliable and powerful new analysis framework for the relative smooth problem class.

Job Requirements

Interested applicants are required to possess a BSc. in 2026. He/she should have a good understanding in

1.    convergence and complexity analysis for (nonconvex) optimization algorithms  
2.    stochastic process and stochastic approximation methods

In particular, as this is a research assistant position for only 1 year. The applicant should be experienced in MATLAB and Python coding. In particular, he/she should have the ability to adapt base codes of PyTorch to implement new algorithms instead of calling built-in functions.

As we plan to apply our methodologies to the training and tuning of language models, it will be an advantage if the applicant has related experience. 

Job Description

•                    Ensures proper investigational product (IP)management which includes sourcing, receipt, storage, preparation, dispensing,labelling, inventory accountability, reconciliation, retention, destruction anddocumentation according to the study protocol

•                    Assists Clinical Research Technologists inmaintaining proper functioning of all pharmacy equipment.

•                    Reviews and provides feedback during protocoldevelopment where applicable

•                    Reviews and updates Pharmacy local standardoperation procedures as appropriate

•                    Provides coaching to Locum Pharmacists andPharmacy Technicians/Assistants as needed on IP management and asepticcompounding

Requirements

•                    Singapore Registered Pharmacist

•                    Previous Hospital Pharmacy Experience

•                    Experience in working in cleanroom ormanufacturing setting

•                    General GMP and GDP knowledge

Interested candidates please send in your resume to:

valerie@recruitexpress.com.sg

EA Personnel: Valerie Yong Kian Fung

CEI No.: R1103704

Recruit Express Pte Ltd, EA License No.: 99C4599

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Multi-ion-%C2%B9%E2%81%B7%E2%81%B6Lu%E2%81%BA-Optical-Clocks%29/33452-en_GB/

We regret that only shortlisted candidates will be notified.

About the Centre for Quantum Technologies (CQT)

The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena. Experts in this new discipline of quantum technologies are applying their discoveries in computing, communications, and sensing.
CQT is hosted by the National University of Singapore. The Centre also has staff at the Agency for Science, Technology and Research, Nanyang Technological University, Singapore, and the Singapore University of Technology and Design. With some 200 staff and students, it offers a friendly and international work environment

Learn more about CQT at https://www.cqt.sg/

Job Description

Single-ion optical clocks are among the most precise instruments ever built — yet they are fundamentally limited by quantum projection noise. The next frontier is multi-ion operation: entangled and correlated ion crystals that deliver the stability of many atoms with the systematic control of a single trapped ion. Our group at CQT is pioneering this approach with ¹⁷⁶Lu⁺ , a species with uniquely low sensitivity to environmental perturbations. This postdoc offers the rare opportunity to work at the intersection of precision metrology, many-body quantum physics, and real-world timekeeping infrastructure.

Key Responsibilities

• Prepare and characterise multi-ion ¹⁷⁶Lu⁺ crystals in a linear Paul trap, developing robust protocols for ion loading and cooling.
• Implement and refine correlated clock interrogation schemes — Ramsey spectroscopy and spin-echo sequences — on ion ensembles to suppress noise below the standard quantum limit.
• Develop quantum state preparation and readout techniques optimised for multi-ion clock operation, including high-fidelity fluorescence detection of large crystals.
• Characterise and suppress collective systematic shifts in multi-ion configurations, contributing to a rigorous uncertainty budget for the ¹⁷⁶Lu⁺ clock transition.
• Explore entanglement-assisted sensing protocols and their practical implementation in a metrological context.
• Contribute to publications, conference presentations, and the broader activities of the CQT Lu+ clock programme.

Qualifications

• PhD in AMO physics, quantum optics, or a closely related field, completed or near completion.
• Hands-on experience with ion trapping, laser cooling, or precision spectroscopy in an experimental AMO setting.
• Familiarity with coherent control techniques: Ramsey spectroscopy, motional sideband manipulation, or quantum gate operations on trapped ions.
• Strong experimental instincts — ability to diagnose and solve complex technical problems independently.
• Experience with Python-based experiment control or real-time digital feedback systems is advantageous.
• A track record of research output commensurate with career stage.

Additional Information

What we offer:

• Competitive NUS postdoctoral salary.
• 2+1 years, renewable based on performance
• World-leading AMO group at the NUS campus.

To apply, please submit a CV, a brief cover letter (1 page) describing your relevant experience and motivation, and the names of two referees. Applications are considered on a rolling basis. Inquiries should be directed to Prof. Murray Barrett at phybmd@nus.edu.sg

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Relative-smooth-optimization-theory%29/33458-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

In recent decades, we have witnessed significant progresses in the convergence and complexity theory of the first-order optimization methods, with gradient global Lipschitz continuity (GGLC) assumption playing a central role, in many classical results. However, a large class of important problems arising in modern optimization and machine learning do not satisfy this assumption. As a result, there remains a substantial gap between the theory and practical behavior of many widely used algorithms.

This project, led by Dr. Zhang, aims to strengthen the theoretical foundation of relative smooth optimization, an emerging framework developed to go beyond the classical GGLC setting. In particular, the project will study first-order methods under relative smoothness, with a focus on nonconvex problems, more appropriate optimality measures, and new non-Euclidean Lipschitz tools that better capture the underlying problem geometry. The goal is to establish sharper convergence and complexity results, clarify several widely adopted but potentially misleading arguments in the current literature, and develop a more reliable and powerful new analysis framework for the relative smooth problem class.

Job Requirements

Interested applicants are required to possess a PhD in 2026. He/she should have a good understanding in

1.    convergence and complexity analysis for (nonconvex) optimization algorithms 
2.    variational inequalities and duality theory
3.    stochastic process and martingale theory
4.    semi-algebraic and subanalytic geometry
5.    stochastic approximation methods
6.    dynamical systems

The applicant should also be experienced in MATLAB and Python coding. In particular, he/she should have the ability to adapt base codes of PyTorch to implement new algorithms instead of calling built-in functions.

In addition, experience in GPU-based acceleration of large-scale algorithms will be an advantage. Familiarity with implementing or adapting first-order methods on GPU platforms, as well as handling large-scale matrix-vector computations efficiently, is preferred.

NOTE: This grant contains 2 research fellow positions, while each job posting will create 1 job. Thus, there will be 2 identical jobs posted. Please submit your applications to both of the posts. 

Job Summary

About the Role

The Institute of High Performance Computing (IHPC), A*STAR, is seeking a highly motivated Research Engineer to develop and deploy advanced AI systems that translate cutting-edge research into scalable real-world applications.

The successful candidate will work closely with research scientists to implement, optimize, and operationalize AI models across healthcare and biomedical domains. This role combines software engineering, machine learning, and systems engineering to bridge the gap between research and deployment.

Key Responsibilities

AI System Development

• Design, develop, and maintain machine learning and deep learning systems.
• Implement state-of-the-art AI algorithms from research prototypes into production-quality software.
• Build scalable data processing and model training pipelines.
• Develop multimodal AI systems integrating text, image, video, sensor, and structured data.
• Optimize model training, inference, and deployment workflows.

Research Translation

• Collaborate with AI researchers to translate novel algorithms into robust software solutions.
• Reproduce and benchmark research models.
• Develop reusable AI frameworks, libraries, and tools.
• Support experimentation, model evaluation, and performance optimization.

Software & Infrastructure Engineering

• Design scalable cloud and on-premise AI infrastructure.
• Develop APIs, backend services, and model-serving platforms.
• Implement automated testing, monitoring, and CI/CD pipelines.
• Support large-scale distributed training and inference systems.

Deployment & Integration

• Deploy AI solutions into healthcare, scientific, and enterprise environments.
• Integrate AI systems with operational workflows and external platforms.
• Develop monitoring tools for model performance and reliability.
• Support technology transfer and production deployment activities.

Requirements

Essential

• Bachelor's or Master's degree in Computer Science, Computer Engineering, Artificial Intelligence, Data Science, or related disciplines.
• Strong programming skills in Python.
• Experience with PyTorch, TensorFlow, or similar machine learning frameworks.
• Experience in software engineering best practices.
• Familiarity with Linux, Git, and software development workflows.
• Strong problem-solving and system design skills.

Preferred

• Experience with:Large Language ModelsMultimodal AIComputer VisionMLOps platformsCloud Computing (AWS, Azure, GCP)Containerization (Docker, Kubernetes)Distributed ComputingGPU Computing

What We Offer

• Opportunity to work on cutting-edge AI technologies with real-world impact.
• Access to world-class computational infrastructure and research facilities.
• Collaboration with leading researchers, clinicians, scientists, and industry partners.
• A dynamic environment supporting innovation, learning, and career growth.

The Signature Research Programme in Emerging Infectious Diseases (EID) aims to pioneer our understanding of emerging infections through world-class research that integrates immunology, infection biology, pathogen genomics, and computational approaches. This integration drives comprehensive studies of host–pathogen interactions across molecular, individual, and population scales to address emerging health challenges. 
The Coronavirus Lab, led by Assistant Professor Mart Lamers within the Signature Research Programme in Emerging Infectious Diseases (EID), is seeking a full-time Research Fellow / Senior Research Fellow in Computational Biology. Our group leverages cutting-edge technologies—including organoids, CRISPR/Cas9, single-cell and spatial omics—to study coronavirus–host interactions that influence pandemic potential and disease pathogenesis.

We welcome applications from candidates with a strong background in computational and quantitative biology. The successful candidate will play a key role in analysing high-dimensional datasets and fostering an interdisciplinary research environment at the interface of virology, genomics, and data science.

We are looking for a creative, innovation-driven individual who is eager to uncover hidden patterns within complex datasets—insights that can both strengthen our experimental findings and spark bold, testable hypotheses that push the boundaries of discovery in our lab. This role also offers the freedom to develop quantitative AI/ML pipelines for pathogen risk assessment, informed by insights from our wet lab scientists.

Main Responsibilities

• Perform tasks and support all aspects of the research project.
• Carry out algorithm development and data analysis, including (but not limited to) single-cell and bulk transcriptomics, spatial omics, proteomics, and genome-wide association (GWAS) data independently.
• Lead AI/ML-driven efforts to develop pathogen risk assessment pipelines.
• Collaborate with experimental scientists to integrate computational findings with biological hypotheses.
• Contribute to scientific writing and dissemination of results through publications, presentations, and grant proposals.
• Mentor junior lab members and contribute to collaborative team science efforts.
• Perform other related duties incidental to the work described therein.

Job Requirements

• PhD Degree in a related scientific area (e.g., Bioinformatics, Computational Biology, Machine Learning/AI, Computer Science, Virology, Cell biology, or Immunology) with demonstrated hands-on experience in developing and/or applying algorithms for multi-omics data integration.
• Proven proficiency analysing bulk and single-cell transcriptomic datasets.
• Proficiency in R and/or Python coding.
• Familiarity with high-performance computing (HPC) environments and GPU programming.
• Have experience with spatial omics or GWAS analysis is strongly advantageous.
• Experience with AI/ML approaches for biological data analysis would be advantageous.
• Have excellent quantitative, analytical, and organizational skills.
• Collaborative, motivated, and adaptable, with a commitment to open and integrative team science.

We regret that only shortlisted candidates will be notified.