Total 16 Education / Training job vacancies

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

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-%28Quantum-Engineering%29/33413-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are seeking a highly motivated Research Fellow to join our growing team developing next-generation electrical interfaces to diamond quantum sensors based on nitrogen-vacancy (NV) centers. The successful candidate will lead efforts to develop novel electrical readout, control, and sensing architectures that complement or potentially replace conventional optical detection methods.

The research will combine semiconductor device physics, quantum sensing, spin-dependent transport, and diamond electronics, with opportunities to explore hybrid platforms involving two-dimensional materials, field-effect devices, and advanced electrical detection techniques.

Key Responsibilities

•    Electrical interfaces for diamond quantum systems: Lead efforts to develop and optimize electrical approaches for detecting and controlling NV-center spin and charge states, including device design, fabrication, and characterization.
•    Semiconductor device architectures: Explore p-i-n, Schottky, field-effect, and related device structures for integrating diamond defects with electrical readout and control platforms.
•    Spin-dependent transport and recombination: Investigate spin-dependent electrical, optical, and recombination processes in diamond and related defect systems for quantum sensing applications.
•    Diamond–hybrid devices: Develop hybrid device architectures incorporating diamond with novel and/or CMOS-compatible materials, including graphene, silicon nitride, or other functional layers for electrical transduction.
•    Device modelling and simulation: Model carrier transport, charge-state dynamics, photoelectric processes, recombination pathways, and electrostatic device behaviour to guide experiments and optimize device performance.
•    Team collaboration and mentorship: Work closely with PhD students, research engineers, and undergraduate researchers while contributing to the growth of a multidisciplinary research programme.
•    Cross-disciplinary exploration: Engage with applications spanning quantum sensing, integrated electronics, semiconductor diagnostics, quantum materials, and bioelectronic sensing.

What We Offer
•    Opportunity to pioneer new approaches to electrical quantum sensing and spin-based technologies in diamond.
•    Access to state-of-the-art facilities for diamond characterization, device fabrication, optics, microwave engineering, and electrical measurements.
•    Freedom to pursue ambitious and innovative research directions at the intersection of quantum technology, semiconductor electronics, and advanced sensing.
•    Participation in building a new research programme from the ground up, with significant opportunities for intellectual leadership, technology development, and independent project ownership.
•    Strong emphasis on translation beyond academic publications, including the development of enabling technologies, prototype systems, intellectual property, and real-world sensing applications.
•    Opportunities to contribute to patent generation, technology commercialization, industry partnerships, and potential future spin-out ventures arising from the research.
•    Exposure to a broad range of application areas, including semiconductor diagnostics, advanced manufacturing, quantum instrumentation, materials characterization, healthcare technologies, and next-generation sensing systems.
•    Collaboration with experts across quantum sensing, nanofabrication, semiconductor devices, materials science, photonics, and engineering.
•    Strong support for publishing impactful research while simultaneously pursuing technologies that can deliver tangible scientific, industrial, and societal benefits.

Job Requirements

Job Requirements
•    PhD in Physics, Electrical Engineering, Materials Science, Applied Physics, or a closely related field.
•    Strong background in one or more of the following:
     o   Semiconductor device physics
     o   Quantum sensing or spin physics
     o   Diamond defects and color centers
     o   Electronic transport measurements
     o   Semiconductor characterization techniques
•    Experience with electrical device fabrication and characterization, including Schottky diodes, p-i-n structures, FETs, or related semiconductor devices.
•    Familiarity with low-noise electrical measurements, RF electronics, lock-in techniques, impedance spectroscopy, capacitance measurements, or microwave spin-resonance methods.
•    Experience with carrier transport simulations, semiconductor modelling, finite-element analysis, or device design tools is advantageous.
•    Knowledge of NV centers, spin-dependent recombination, charge-state physics, PDMR, ODMR, or related quantum defect systems is desirable but not strictly required.
•    Experience with graphene, hBN, other two-dimensional materials, or hybrid quantum-semiconductor devices would be highly advantageous.
•    Strong publication record, scientific communication skills, and ability to work independently while contributing effectively within a collaborative team.
•    Open to Fixed Term Contract.

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-Associate-%28Data-Engineering%29/33302-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are seeking a skilled and motivated Research Associate to join our environmental informatics team. In this role, the candidate will build and maintain the data infrastructure that underpins our environmental monitoring and early-warning systems. The work will involve diverse, high-volume data streams — including rainfall records, temperature sensors, radar imagery, and computer vision outputs — to deliver a unified, query table, and secure data platform that drives research, operational decision-making, and stakeholder dashboards. 

Key Responsibilities
1.  Environmental Data Platform
•    Design, build, and maintain a unified database to ingest and store diverse environmental data streams: rain gauge records, gridded temperature data, rainfall radar (e.g. OPERA, NEXRAD), satellite imagery, and computer vision model outputs.
•    Define and enforce common data schemas and ontologies across heterogeneous source formats (NetCDF, HDF5, GeoTIFF, CSV, JSON, REST/API feeds).
•    Implement scalable ingestion pipelines supporting real-time streaming and batch historical loads.
•    Ensure data traceability with robust metadata, provenance tracking, and versioning.

2.  Data Processing & Quality Assurance
•    Develop and maintain automated pipelines for data cleaning, outlier detection, and quality flagging.
•    Implement missing-data imputation methods appropriate to environmental time-series and spatial fields (e.g. interpolation, climatological fill, ML-based gap-filling).
•    Apply noise-removal algorithms (e.g. signal filtering, radar clutter suppression, spike detection) across sensor and remote-sensing data types.
•    Document processing logic and maintain reproducible workflow configurations. 

3.  Visualisation & Dashboards
•    Design and develop interactive dashboards for operational and research users, displaying spatial maps, time-series plots, and aggregated statistics.
•    Integrate visualisation tools (e.g. Grafana, Superset, Plotly Dash, or custom web front-ends) with the data backend.
•    Collaborate with domain scientists to translate monitoring requirements into effective visual analytics.
•    Ensure dashboards remain performant and responsive under live data load. 

4.  Data Security & Governance
•    Implement and maintain role-based access control (RBAC) for all data assets.
•    Enforce data encryption at rest and in transit; manage secrets and credentials securely.
•    Support compliance with relevant data governance policies and institutional data-sharing agreements.
•    Maintain audit trails and access logs; respond to security reviews and risk assessments.

5.  Infrastructure & Operations
•    Manage cloud or on-premise database services (e.g. PostgreSQL/PostGIS, TimescaleDB, InfluxDB, or equivalent); tune for time-series and geospatial query performance.
•    Maintain CI/CD pipelines for data pipeline code; apply version control best practices.
•    Monitor pipeline health, set up alerting for failures, and respond to incidents.
•    Contribute to infrastructure-as-code practices (Docker, Kubernetes, Terraform or equivalent)

Job Requirements

•    Possess at least a Master’s degree in computer science, Data Engineering, Environmental Informatics, or a closely related field.
•    3–6 years of professional experience in data engineering, with demonstrable work on time-series or geospatial data.
•    Proficiency in Python (pandas, NumPy, xarray, or similar) and SQL; experience with at least one workflow orchestration tool (Airflow, Prefect, Luigi, etc.).
•    Hands-on experience with geospatial or scientific data formats: NetCDF, HDF5, GeoTIFF, GeoJSON, or similar.
•    Working knowledge of relational and time-series databases, with practical experience in data modelling.
•    Familiarity with cloud platforms (AWS, GCP, or Azure) and containerisation (Docker).
•    Solid understanding of data security principles: encryption, RBAC, secrets management. 
•    Open to fixed-term contract. 

Experience
•    Experience with environmental, meteorological, or hydrological datasets (radar QPE, NWP outputs, IoT sensor networks).
•    Familiarity with PostGIS or other spatially enabled database extensions.
•    Exposure to machine learning pipelines or MLOps practices for model output ingestion.
•    Experience building dashboards with Grafana, Apache Superset, Plotly Dash, or equivalent.
•    Contributions to open-source scientific data tooling (e.g. xarray, GDAL ecosystem).

Core Competencies
•    Preferably knowledge with Python, SQL, Bash
•    Time-series & geospatial DBs
•    Data pipeline orchestration
•    Cloud & containerisation
•    Dashboard & BI tools
•    Data security & RBAC

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-%28Dept-of-Materials-Science-and-Engineering%29-1/30162-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are looking for highly talented and motivated candidates to work on developing closed loop robotics hardware and software. Together with a multi-disciplinary team of electronics/electrical engineers, you will be part of an exciting research program to develop next-generation sensor devices and systems for human-machine interactions. 

Qualifications

PhD in Materials Sciences, Robotics, Mechanical Engineering, or related disciplines.

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-Associate-%28MET-Product-Development-Timber-Engineering%29/33264-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Department of Architecture, Department of Civil and Environmental Engineering, and Department of Built Environment are jointly conducting research on harnessing regional tropical timber/bamboo for sustainable and durable mass engineered timber (MET) products for the Tropics. We are looking for one candidate who can contribute in the following areas:

•    Prototyping and Adhesive Testing
•    Timber/Bamboo Grading and lamellar strength determination/classifications guidelines
•    Range of product sizes and configurations and their respective design data/properties for Glulam / CLT / Laminated Bamboo Lumber (LBL)
•    Factory production control and audit practices / requirements
•    Assist in technical studies on the different timber and non-timber /MET products
•    Assist in preparing manuscripts for academic journal articles, filing of patents and/or conference presentations.
•    Assist PI and Co-PIs in general administrative management of the research project.

Duration of Appointment:
Up to 2 years contract, with possibility of renewal.

Gross Monthly Salary Range:
Salary will be commensurate with the candidate’s qualification and experience.

Estimated no. of work hours per week:
42 h/week (Fulltime appointment)

Qualifications

Essential requirements:
- Qualified to Master level or higher degree in MET Product Development / Timber Engineering and/or related discipline.
- At least 2 years’ relevant work experience and good knowledge, skills and expertise in relevant field
- Demonstrated ability to conduct and publish high-quality research
- Strong analytical, writing, and communication skills in English, and able to produce clear reports/recommendations
- Strong project execution skills, including procurement/logistics coordination
- Experience with MET product development (min. 1 year).
- Excellent communication skills with diverse collaborators and specialists.
- Ability to work independently.

Added Advantage:
- Familiarity with Asia-Pacific forestry industries and/or tropical timber/bamboo species and markets
- Basic knowledge of Bahasa Malay, Bahasa Indonesia, Japanese or Chinese for communication with Asian foresters / manufacturers
- Proven experience engaging industry stakeholders to obtain data and information

Application deadline:
15th Jul. 2026 (Till the position filled).

Application
Please consolidate the following documents as one PDF document and email it to the NUS Career Portal. Kindly indicate “Application to Research Associate (MET Product Development / Timber Engineering)” in the email subject title
a)    Cover letter
b)    Curriculum Vitae (CV) including full publication list and last drawn salary
c)    Personal Statement (one page) about research interest, career goals, relevant experience and motivations for applying for this position, and
d)    Names and contact information of 3 references (PhD supervisor or collaborators are allowed)

Appreciate your understandings in advance that only selected qualified applicants will receive responses. Shortlisted candidates may also be asked to submit additional documents for our considerations, if necessary.

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-%28Machine-Learning-and-Optimization-in-Chemical-Engineering%29%2C-ChBE/33284-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Research Engineer 

•    will work closely with the Principal Investigator on several research projects on using machine learning in chemical and optimization problems 

•    will help to develop machine learning models for both theory and applications in advanced control systems 

Job Requirements

•    B.S. or M.S degree in a relevant area, e.g., Chemical Engineering, Control Engineering, Computer Science,  Chemistry, etc.
•    Experienced in machine learning, optimization and programming languages (e.g., python, Matlab, C++, etc)
•    Any experience with 1) advanced control and optimization, 2) machine learning theory and applications, and 3) chemical engineering and chemistry is a plus

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-%28Machine-Learning-and-Optimization-in-Chemical-Engineering%29%2C-ChBE/33281-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Research Engineer 

•    will work closely with the Principal Investigator on several research projects on using machine learning in chemical and optimization problems 

•    will help to develop machine learning models for both theory and applications in advanced control systems 

Job Requirements

•    B.S. or M.S degree in a relevant area, e.g., Chemical Engineering, Control Engineering, Computer Science,  Chemistry, etc.
•    Experienced in machine learning, optimization and programming languages (e.g., python, Matlab, C++, etc)
•    Any experience with 1) advanced control and optimization, 2) machine learning theory and applications, and 3) chemical engineering and chemistry is a plus

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-%28Offshore-Geotechnical-Engineering%29/33194-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Research Fellow (RF) will be responsible for leading and managing research activities related to the project titled Offshore Geotechnical Engineering. 

Key duties include conducting offshore soil- structure cyclic loading for Coastal Structures and supervising research assistants and ensuring compliance with safety and ethical standards and contributing to the preparation of progress reports and grant documentation.

Qualifications

•    Possess at least a PhD degree in relevant fields include Civil Engineering, Ocean Engineering, Fluid Mechanics, Computer Science, or related disciplines. Applied Mathematics, Data Science, Electrical and Electronics Engineering, Earth Sciences, Remote Sensing, and Artificial Intelligence are also well-suited. (More details on PhD requirements can be found at: https://nusgs.nus.edu.sg/scholarships/nus-research-scholarship/)
•    Strong written and spoken communications. 
•    Demonstrated strong research interest, skills, and experience.
•    Proficiency in programming languages (e.g., Python, MATLAB) and experience with data analysis tools.
•    Ability to work both independently and collaboratively within a multidisciplinary team.
•    Open to fixed-term contract. 

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/Assistant-Manager%2C-Contracts-&-Admin-Management/33092-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The candidate will be responsible for developing printable inks based on natural material-derived precursors, such as natural materials-derived calcium phosphate, or related biomineral materials. The work will involve optimizing ink rheology, printability, shape fidelity, and structural stability for extrusion-based 3D printing. The candidate will also design and fabricate porous scaffold architectures with controlled pore size, porosity, and interconnectivity, while optimizing printing parameters such as nozzle size, extrusion pressure, printing speed, and layer height.

A key part of the project will involve post-processing and material conversion of the printed constructs. The candidate will develop and optimize sintering or thermal treatment protocols to convert printed structures into bone-relevant ceramic phases. Through this process, the candidate will help tune the phase composition and mechanical performance of the scaffolds, with the goal of producing reproducible and scalable bone implant prototypes.

Qualifications

•             Bachelor’s degree in mechanical engineering, materials science, or a related field

•             Demonstrated experience in material characterization

•             Team player, able to work collaboratively in a team environment

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-%28Department-of-Materials-Science-and-Engineering%29/33184-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Perform research in high-throughput operando imaging

Qualifications

The successful candidate should possess the following:
•    A PhD in Materials Science, Chemical Engineering, Chemistry, Physics, or related fields
•    Highly motivated, committed, and capable of working independently as well as collaboratively
•    Strong publication record in peer-reviewed journals
•    Good communication skills in English (both written and oral)
•    Prior experiences with the following will be a plus
•    Optical instrumentation, single-molecule/ super-resolution microscopy, magnetic/optical tweezers, ultrafast spectroscopy, or other in-situ operando imaging tools
•    Machine learning for materials discovery or quantitative image analysis, DFT calculations for catalyst design, experiences with MATLAB / Python / AutoCAD / COMSOL
•    Organic synthesis, polymer chemistry, synthesis of inorganic nanomaterials, micro/nano-fabrications, genetic engineering of microorganisms
•    Techno-economic analysis of sustainability technologies

For postdoctoral fellows, compensation and benefits package will be internationally competitive (including annual base salary, performance-based bonus, medical insurance and vacation leave), and will be commensurate with experiences and qualifications. 

Interested candidates are encouraged to email a copy of CV (with a list of publications), reprints of three selected publications, as well as contact information of 2-3 references to the NUS Career Portal.

Interested applicants are invited to apply directly at the US 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-%28Department-of-Materials-Science-and-Engineering%29/33183-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Perform research in neuromorphic computing devices.

Qualifications

The successful candidate should possess the following:
•    A PhD in Materials Science, Chemical Engineering, Chemistry, Physics, or related fields
•    Highly motivated, committed, and capable of working independently as well as collaboratively
•    Strong publication record in peer-reviewed journals
•    Good communication skills in English (both written and oral)
•    Prior experiences with the following will be a plus
•    Optical instrumentation, single-molecule/ super-resolution microscopy, magnetic/optical tweezers, ultrafast spectroscopy, or other in-situ operando imaging tools
•    Machine learning for materials discovery or quantitative image analysis, DFT calculations for catalyst design, experiences with MATLAB / Python / AutoCAD / COMSOL
•    Organic synthesis, polymer chemistry, synthesis of inorganic nanomaterials, micro/nano-fabrications, genetic engineering of microorganisms
•    Techno-economic analysis of sustainability technologies

For postdoctoral fellows, compensation and benefits package will be internationally competitive (including annual base salary, performance-based bonus, medical insurance and vacation leave), and will be commensurate with experiences and qualifications. 

Interested candidates are encouraged to email a copy of CV (with a list of publications), reprints of three selected publications, as well as contact information of 2-3 references to the NUS Career Portal.

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28MaterialsChemistryEngineering%29/32557-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are looking for a passionate and self-motivated postdoctoral research fellow to join our multidisciplinary team working on the development of novel synthetic and bio-based polymers and composite materials for environmental sustainability applications. The successful candidate will be expected to be part of the research team under the supervision of the Principal Investigator (PI) to work on:

• Developing materials and technologies for resource recovery from seawater desalination processes.
• Conducting research and experiments for materials synthesis, fabrication, testing and characterization.
• Writing and preparing progress reports, manuscripts, and proposals related to the propjets.
• Assisting the PI in guiding junior researchers, graduate students, and undergraduate students.
• Assisting the PI in managing projects and laboratories and other ad hoc tasks that may be assigned by the PI.

Qualifications

• A PhD degree in Materials, Chemistry, Chemical Engineering, Environmental Engineering, Bioengineering, or any other related field, obtained from a reputable university.
• Fresh PhD without postdoctoral working experience is welcomed, but showing evidence of excellent research accomplishments.
• Excellent research publication records in reputable international journals.
• Strong background in biomass and bio-based polymers, hydrogels, and composite resins.
• Good written and spoken English communication skills.
• Being a good team player across multiple disciplines.

Job Summary

We are a project team comprising researchers from SingHealth, A*STAR, and Synapxe, developing a product to enhance the management and treatment of patients with lower respiratory tract infections (LRTIs)—a condition that accounts for nearly 489 million cases globally and is a major contributor to inappropriate antibiotic use in Singapore. 

Over 40% of prescriptions for LRTIs are unnecessary, contributing to antimicrobial resistance (AMR)—a top global health threat. Traditional stewardship programs are expert-dependent and resource-intensive, limiting scalability.

To overcome these challenges, we are building an AI-powered Large Language Model platform that uses routinely collected clinical data to help clinicians identify cases that do not require antibiotics, thereby reducing unnecessary prescriptions.

Role:

As a Research Officer, you will play a central role by integrating Large Language Models (LLMs) for intelligent processing of unstructured clinical text—such as physician notes, discharge summaries, and radiology reports. Your work will help build explainable, scalable, and real-time AI recommendations that assist clinicians at the point of care for lower respiratory tract infections.

Key Responsibilities:

• Contribute to the LLM development, focusing on enhancing unstructured data processing for clinical and biomedical applications.
• Fine-tune and train LLMs (e.g., LLaMA, Mistral, Phi, and the GPT family) using supervised and instruction-based datasets.
• Design and implement pipelines for data cleaning, preprocessing, and tokenisation of large-scale text corpora.
• Integrate retrieval-augmented generation (RAG) and knowledge graph components for domain adaptation.
• Evaluate model performance using BLEU, ROUGE, BERTScore, and factual consistency metrics.
• Develop optimised PEFT/LoRA/QLoRA fine-tuning frameworks for efficiency on GPU clusters.
• Collaborate with researchers to design experiments, interpret results, and publish findings.
• Maintain reproducible codebases, documentation, and experiment logs.

Requirements:

• Master or Bachelor in computer science, data science, artificial intelligence, computational linguistics, or related disciplines.
• Strong experience in Natural Language Processing (NLP), transformer-based models, and text generation.
• Proficiency in Python, PyTorch, Hugging Face, Transformers, and LLM fine-tuning libraries (e.g., PEFT, DeepSpeed, bitsandbytes).
• Experience with text and data processing, including annotation, tokenisation, and augmentation.
• Familiarity with vector databases (FAISS, Qdrant) and RAG pipelines.
• Understanding of GPU-based training, distributed model optimisation, and experiment tracking (e.g., MLflow, W&B).
• Strong analytical, communication, and collaborative skills.

Preferred Experience

• Research experience with open-weight LLMs or domain-specific adaptation (e.g., biomedical).
• Experience with multi-agent frameworks, prompt engineering, or LLM safety evaluation.
• Familiarity with cloud computing (AWS, Azure) or on-prem GPU clusters.

What We Offer

• Opportunity to work on cutting-edge LLM research with measurable real-world impact.
• Access to high-performance GPU infrastructure and interdisciplinary collaborations.
• Mentorship and opportunities for publication, conference presentation, and project leadership.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. 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-Associate-%28Machine-Learning-in-Chemical-Engineering%29%2C-ChBE/32386-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

•     The Research Associate will work closely with the Principal Investigator on several research projects on using machine learning in chemical and optimization problems 
•    The Research Associate  will help to develop machine learning models for both theory and applications in advanced control systems 

Job Requirements

•    A Bachelor or Master degree in a relevant area, e.g., Chemical Engineering, Control Engineering, Computer Science,  Chemistry, etc.
•    Experienced in machine learning, optimization and programming languages (e.g., python, Matlab, C++, etc)
•    Any experience with 1) advanced control, 2) machine learning theory and applications, and 3) chemical engineering and chemistry is a plus

This is an exciting opportunity to join an early-stage biotech venture working at the forefront of yeast fermentation. As a Research Intern, you will support ongoing R&D efforts in strain engineering and bioprocess development to enable the production of innovative lipid ingredients via precision fermentation.

You will work closely with the CTO, Senior Strain Engineer, and broader technical team, gaining hands-on experience in genetic engineering, microbial cultivation, and experimental design in a fast-paced startup environment.

Job Description:

• Support routine laboratory operations, including keeping well-organized experimental records and preparation and maintenance of strains, reagents, and consumables
• Execute day-to-day experimentation, including molecular biology workflows and strain screening
• Assist in the design, construction, and testing of engineered microbial (yeast) strains
• Support lipid and fatty acid characterization through analytical assays
• Contribute to ongoing strain engineering and fermentation optimization projects

Ideal Qualifications:

• Currently pursuing or recently completed a Bachelor’s degree in Bioengineering, Chemical Engineering, Microbiology, Molecular Biology, or a related field
• Basic laboratory experience in molecular biology, microbiology, or biochemical engineering
• Familiarity with yeast systems or microbial fermentation is a plus
• Exposure to genetic engineering techniques (e.g.,cloning, transformation, CRISPR) is advantageous
• Singaporean and Singapore PR applicants only

Ideal Skills and Attributes:

• Strong interest in strain engineering, synthetic biology, and industrial biotechnology
• Good foundational knowledge in biochemistry and microbial metabolism
• Detail-oriented with good record-keeping and organizational skills
• Eagerness to learn, take initiative, and work in a fast-paced research environment
• Strong communication and teamwork skills

Location: The position is based out of Singapore. Singaporean and Singapore PR applicants only.

Application: Please send your resume and a cover letter outlining why you’d be interested in this position to shen@terraoleo.com with email subject "Research Intern 2026 - [Your Name]." Compensation will be commensurate with similar research internship roles.

About Terra Oleo:

Terra Oleo is a Singapore-based biotech venture harnessing microbial fermentation to develop sustainable alternatives to conventionally palm oil–derived ingredients and cocoa butter, with the goal of decarbonizing and advancing industries such as personal care, home care, food, and pharmaceuticals.

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/Visiting-Research-Fellow-%28National-Centre-for-Engineering-Biology%29/32344-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are seeking a talented Visiting Research Fellow to join the National Centre for Engineering Biology, Singapore (NCEB), at the National University of Singapore. NCEB aims to advance engineering biology by developing microbial cells that enable biomanufacturing.

The Visiting Research Fellow (RF) will work closely with the Principal Investigator and research team to develop robust microbial cell platforms for biomanufacturing. The RF will design and implement strain engineering strategies, optimise metabolic pathways and cultivation conditions, and generate high-quality experimental data.

Key Responsibilities: 
1. Design, build, and characterise engineered microbial strains for production of target molecules (e.g., enzymes, chemicals, or biomaterials).
2. Develop and optimise genetic constructs and genome engineering workflows (e.g., CRISPR, recombineering, plasmid design, promoter/RBS tuning).
3. Perform metabolic pathway design and optimisation using rational design and/or high-throughput approaches; analyse data to identify bottlenecks and improvement opportunities.
4. Develop and apply analytical assays (e.g., HPLC/GC, LC-MS, plate-based assays) to quantify key metabolites.
5. Document and communicate results through lab records, reports, and presentations; contribute to manuscripts, protocols, and (where applicable) invention disclosures.

Remuneration will be commensurate with 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). Only shortlisted candidates will be notified.

Qualifications

The ideal candidate will:
1. Hold a PhD in Synthetic Biology, Microbiology, Biotechnology, Bioengineering, Chemical Engineering, or a related field.
2. Demonstrated experience in microbial strain engineering and molecular biology (e.g., cloning, genome editing, strain construction and verification).
3. Strong experimental design and data analysis skills, with the ability to interpret results and troubleshoot across the build-test-learn cycle.

Highly desirable:
1. Hands-on experience with fermentation/bioreactors and bioprocess development (media optimisation, feeding strategies, scale-down models).
2. Experience with omics/automation tools (e.g., RNA-seq, proteomics, metabolomics, high-throughput screening).