Total 123 job vacancies by A*star Research Entities

Job Description

A Senior Scientist with a strong chemistry background and at least 5-10 years of related research experience is required to lead the chemistry aspects of themineralization scale-up. This role is critical to ensure deep understanding of reaction mechanisms, accurate optimisation of CO₂ mineralisation, and reliable translation of laboratory results to pilot scale. The position will also ensure robust analytical validation and compliance with NEA standards, reducing technical risks during scale-up.

KeyRoles and Responsibilities

• Lead optimisation of CO₂ mineralisation reaction chemistry and kinetics
• Design and oversee advanced laboratory and testbed studies
• Conduct and interpret detailed material characterisation (e.g., XRD, ICP-MS, TGA)
• Provide expert support for pilot plant troubleshooting and process refinement
• Ensure product safety and compliance with regulatory requirements
• Collaborate with engineering teams to integrate chemistry insights into scale-up design

JobRequirements

• Degree: PhD in chemistry or related fields with experience in applied research or industry collaboration preferred
• Proven experience in project management and leading research teams
• Good understanding of chemical processes and their design and optimization.
• Good understanding of chemistry and chemical engineering concepts, particularly in (but not limited to) inorganic chemical synthesis and multiphase reactions.
• Experience in designing, setting up and operating reactors and other equipment at the kg-scale.

Remarks:

This role is essential for bridging laboratory research and pilot-scaleimplementation, ensuring successful translation of the CCUS and technology towards commercial deployment.

About the Job

The Institute of Sustainability for Chemicals, Energy and Environment (ISCE2) was established by A*STAR in 2022 to support Singapore's decarbonisation and sustainability goals, through strong international partnerships with industry, public agencies, and academia. ISCE2 is located at Jurong Island.

The Senior Manager / Assistant Director / Senior Assistant Director (Technology‑Business Development – Low‑Carbon Hydrogen) will manage industry R&D collaborations and translation activities across hydrogen and hydrogen‑derived value chains (e.g. production, storage, carriers such asammonia, cracking, utilisation and systems integration). In addition to driving execution, the role contributes to A*STAR’s technical and strategic positioning in low‑carbon hydrogen by shaping translation roadmaps, articulating evidence‑based perspectives to industry and public agencies, and influencing ecosystem‑level directions across hydrogen and hydrogen‑derived value chains.

The role supports the end‑to‑end technology‑business lifecycle, from early project scoping and IP strategy through to commercialization, licensing, and scale‑up, strengthening Singapore’s National Decarbonization Grand Challenge. Success in this role is reflected not only in projects delivered and partnerships secured, but also in the clarity, credibility, and influence of A*STAR’s technical viewpoints across the hydrogen ecosystem.

Key Responsibilities

• Manage and grow industry partnerships and collaborative R&D portfolios in low‑carbon hydrogen, delivering against key performance indicators for industry engagement, investment, and translation outcomes. Proactively scope, support, and manage projects across the innovation and translation pipeline, including securing industry contracts, research collaboration agreements, and public‑private partnerships.
• Assess, prioritise, and develop strategies to commercialise A*STAR intellectual property and platform capabilities related to hydrogen systems and technologies. Support and manage IP creation, protection, and deployment, including invention assessments, market analysis, competitive landscaping, and business/IP strategy formulation.
• Track technology and market trends in hydrogen and the broader energy transition landscape to identify opportunities for licensing, spin‑outs, and new collaborations. Engage researchers, industry partners, and public agencies to frame sector‑level challenges, align evidence‑based responses, and influence how emerging hydrogen technologies are assessed, adopted, and scaled.
• Deliver measurable outcomes as an individual contributor while supporting broader team and sector objectives.
• Contribute to the shaping of industrial ecosystems that reduce adoption barriers and accelerate deployment of hydrogen technologies in Singapore and the region. Articulate strategic technology‑translation viewpoints in hydrogen and hydrogen‑derived systems, informed by project outcomes, market intelligence, and regulatory developments, to guide partnerships, IP strategy, and programme priorities.
• Undertake ad‑hoc assignments as required by Decarbonisation Tech‑Biz leadership.

Job Requirements

• Bachelor’s degree or higher in chemical engineering, chemistry, engineering, energy systems, or a related discipline.
• Minimum 5–10 years of experience in technology management, industry partnerships, account management, or innovation/commercialisation roles.
• Experience supporting or managing commercialisation of energy, hydrogen, chemicals, or sustainability‑related technologies with MNCs, local enterprises, or start‑ups is preferred.
• Familiarity with intellectual property management, including identification, due diligence, and protection, is an advantage.
• Strong stakeholder engagement, communication, and negotiation skills.
• Ability to navigate complex technology development lifecycles from research to commercial deployment.
• Strategic thinker with good judgement and execution discipline in a fast‑moving, multi‑stakeholder environment.

Job Description

The Senior Scientist will lead the commissioning, installation and operation ofcontinuous flow equipment and instrument within the AiXL lab.

 Key Roles and Responsibilities:

Acquisition and installation of continuous flow equipment

• Procurement of commercially available modular units that can be assembled to create bespoke continuous flow workflow, including homogeneous and multiphasic reactions
• Implement of appropriate inline analytics to capture real-time data.
• Adopt necessary hardware and software to automate the system and to capture data.

Workflow & Instrument Management

• Establish SOP for different workflows, including thermal chemistry, photochemistry, etc
• Develop new data analytical tools (hardware and software) to expand beyond existing capabilities.

Technical Support & Synergy

• Familiar with Design of Experiments (DoE) and Bayesian Optimization.
• Conduct laboratory personnel training and certify authorized users on continuous flow experiments.

Operational Excellence

• Ensure strict compliance with Health, Safety, and Environment (HSE) requirements, including chemical storage and waste disposal.
• Manage procurement operations for laboratory supplies, equipment consumables, and services.
• Participate in R&D project meetings to provide technical insights and progress updates.

Job Requirements
Educational & Professional Experience

• Background: PhD in Chemistry or Chemical Engineering, preferably in continuous flow
• Expertise: Working knowledge in constructing flow reactors, and to collect data using inline analytics.
• Specialization: Proven experience in automation, and data-driven workflow.

Technical Skills

• Programming: Proficiency in Python for data automation and processing is essential.
• Data Science: Familiarity with Design of Experiments (DoE) and Bayesian Optimization workflows.
• Systems: Knowledge of electronic laboratory information systems (LIMS) or digital analytical data handling platforms is a significant advantage.

Soft Skills & Attributes

• Motivation: Highly motivated individual capable of driving the digitalization of traditional laboratory workflows.
• Communication: Strong interpersonal skills for interacting with internal R&D teams and external industry stakeholders.
• Reporting: Ability to produce high-quality written reports and deliver technical presentations.
• Safety Mindset: Uncompromising commitment to laboratory safety and general housekeeping standards.

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

Job Scope

• Design, develop, and execute research projects in membrane science and technology for sustainable and low-carbon separations.
• Develop advanced polymeric membranes, thin-film composite membranes, mixed-matrix membranes, and molecular-sieving membranes by incorporating sustainable polymers, functional nanomaterials, porous fillers, and advanced crosslinking/interfacial engineering strategies.
• Optimize membrane microstructure, free volume, interfacial compatibility, and transport pathways to achieve high permeability, selectivity, and long-term stability under complex operating conditions.
• Conduct membrane fabrication, modification, and performance evaluation for applications such as CO2 capture, H2 purification, vapor/VOC separation, organic solvent separation, resource recovery, and industrial fluid purification.
• Utilize and troubleshoot advanced characterization techniques, including SEM, TEM, AFM, FTIR, XPS, TGA, DSC, DMA, rheology, gas sorption, and permeation measurements, for membrane structure-property analysis.
• Interpret experimental results, compile technical reports, and present research outcomes at project meetings and international conferences.
• Lead the preparation of high-impact manuscripts for top-tier peer-reviewed journals and actively contribute to patent applications and technology translation.
• Conduct comprehensive literature reviews and propose innovative approaches for developing stable, recyclable, scalable, and high-performance membrane materials.
• Assist in mentoring junior researchers, students, and interns, and contribute to collaborative projects with academic and industrial partners.

JobRequirement

• PhD in Chemical Engineering, Materials Science and Engineering, Polymer Science, Chemistry, Environmental Engineering, or a related discipline.
• Strong research background in membrane science and technology, polymer materials, functional materials, or selective separations.
• Prior experience in polymer membranes, thin-film composite membranes, mixed-matrix membranes, molecular-sieving membranes, gas/vapor separation, organic solvent nanofiltration, or membrane transport studies is highly preferred.
• Experience in CO₂ capture, H₂ purification, hydrocarbon separation, vapor/VOC separation, low-carbon separation processes, or membrane stability under humid/complex industrial streams would be an advantage.
• Proficiency in membrane fabrication, membrane characterization, and separation performance evaluation.
• Familiarity with characterization techniques such as SEM, TEM, AFM, FTIR, XPS, TGA, DSC, DMA, rheology, gas sorption, and membrane permeation testing.
• Track record of publishing high-quality papers in membrane science, polymer materials, chemical engineering, or related fields. Experience in patent applications or technology commercialization is an advantage.
• Proven ability to conduct independent research, manage research projects, analyze complex data, and solve technical problems.
• Good scientific writing, communication, and presentation skills.
• Ability to collaborate effectively in multidisciplinary teams and contribute to the supervision of junior researchers.

Job Description

The Genome Institute of Singapore (GIS) is the national flagship for genomic sciences, driving cutting-edge research at the intersection of biology, engineering, and medicine. This position is offered in the Laboratory of AI in Genomics, led by Prof. Mile Šikić, which uses advanced bioinformatics and deep learning approaches to develop next-generation models for genomic data analysis. We are group a of computer scientist with a mission to improve healthcare using advance deep learning models. Located in the heart of Singapore’s thriving biomedical hub, GIS offers a dynamic and collaborative environment, with close ties to world-class universities (NUS and NTU), pharmaceutical companies, and biotech start-ups. Joining our team means working on transformative projects with real-world impact, while benefiting from Singapore’s vibrant research ecosystem and strong support for innovation.

Project background:

De novo genome assembly has been one of the most challenging problems in genomics. However, with development of new long read sequencing technologies, new assemblers and manually curated high quality benchmarks including CHM13, HG002 and I002C assembling most of human chromosomes T2T has become a routine task.

This project will focus on a more challenging task, assembling of human cancer genomes which are especially difficult due to cancer genome heterogeneity. Using the fact that we can reconstruct normal tissue genomes routinely we aim to reconstruct cancer genomes.

Job duties and responsibilities:

We invite brilliant minds in computer science to join us at the cutting-edge of cancer genomics research, harnessing the power of artificial intelligence or classical algorithms. Your job will involve either the development of new algorithms or deep learning models focusing on understanding cancer genomes. The focus will be on de novo genome assembly methods for reconstructing cancer genomes or developing new generative RNA/DNA/epigenome/epitranscriptome foundation models and agents aiming to speed up therapeutics development.

The duties include development of AI models or algorithms.

Job Requirements:

• Bachelor or Master in Computer Science, Mathematics or Physics
• Experienced in deep learning or classical algorithms
• Experienced in Pytorch for deep learning or C/C++ or Rust for classical algorithms
• Experienced with bioinformatics methods and tools for (a) variant calling, and/or (b) de novo assembly and/or (c) long read sequencing analysis;
• Proficiency in Python, and genomics and machine learning libraries therein.
• Keen interest in programming, algorithm development, mathematics, complexity, and puzzles.

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.

We are looking for highly motivated and talented researchers to join our interdisciplinary team working on advanced modelling of complex large-scale urban systems, with a particular focus on land use, transport, and the built environment.

This role will involve developing, applying, and refining computational models to better understand urban dynamics, including how land use and transportation interact with the physical, social, and economic environment.

They will work with a collaborative and interdisciplinary team of scientists and engineers that have a passion in understanding the dynamics of large-scale socio-technical systems such as urban transportation (either land, air and/or sea) as well as the relationship between the built environment and social outcomes (such as health or behavioural outcomes across different population segments).

Shortlisted candidates would have the opportunity to work with various external collaborators, either from government and/or industry and work on high-impact real-world research problems, in which they will apply various computational tools such as modelling and simulation and AI to derive insights that can inform urban policy and planning.

Requirements

• Ph.D in Physics, Engineering, Data Science, Geography, or related fields

• Proficiency in Python or R with experience in geospatial and/or statistical packages

• Relevant research/project experience in either of these fields:

o Spatial analysis / Geospatial information system (GIS)

o Transportation and urban systems

o Agent-based modelling / network analysis

• Demonstrated experience in applying geospatial and/or statistical analysis or other relevant analytics tools on real urban problems would be highly desirable

• Experience working on large scale real-world datasets as well as knowledge of social dimension in urban planning would also be a plus

• Good written and verbal communication skills

• Ability to work effectively in an interdisciplinary research environment both individually as well as in a team, with a strong interest in collaborative research and policy impact

This work contributes directly to strengthening Singapore’s position as a future-ready global aviation hub, enabling more efficient, resilient, and intelligent airport operations through data-driven research and operational innovation.

Job Requirements

• PhD degree in Operations Research, Industrial Engineering, Systems Engineering, Computer Science, Computer Engineering, Data Science, Electrical Engineering, Mechanical Engineering, or a related discipline with rich AI experience.

• Strong programming and data analysis skills, preferably using C/C++, JAVA, or similar.
• Experience in data analysis, cleaning, and visualisation, particularly for real-world sensor data (e.g., surface radar, GPS, and weather data).
• Experience in simulation, optimisation, or decision-support systems applied to transportation or airport operations is highly desirable.
• Experience in process modelling, operational concept development, and workflow analysis for large-scale operational systems.
• Strong background in airport operations, air transport systems, or complex system modelling, with experience in operational analysis and systems-level thinking is a plus.
• Demonstrated ability to conduct independent, high-quality research and translate ideas into deployable prototypes.
• Strong communication and collaboration skills, with the ability to work effectively with domain experts and operational stakeholders.
• A strong sense of ownership, research integrity, and the ability to deliver high-quality work under tight timelines.
• A genuine passion for advancing AI technology and translating research outcomes into real-world operational impact.

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.

At EDDC, our goal is to discover and develop novel therapeutics by working collaboratively with public sector and industry partners. EDDC now has an opening and is seeking to recruit a highly motivated Scientist in the EDDC Academic Research Organisation team. The successful candidate will participate and support inter-disciplinary drug discovery projects through the management of our small molecule compound inventory and our automation systems. This is an exciting opportunity to be a part of the team working on the discovery of novel therapeutics and engaging in preclinical drug development from target exploration to drug candidate selection.
 
Job Description

The compound management scientist oversees the lifecycle of small-molecule compounds and related materials (e.g., fragments, libraries, reference standards) across the organization. This role ensures accurate tracking, efficient distribution, and optimal utilization of compounds to support research, screening, and drug discovery programs. 

The ideal candidate combines expertise in compound management with strong computational and automation skills, enabling data integrity, system efficiency, and continuous process improvement.

Job Scope

Key roles and responsibilities

1. Compound Inventory Management & Oversight:

• Receive, catalogue, and store chemical compounds in a systematic and organized manner, ensuring traceability and quality control throughout their lifecycle.
• Maintain accurate and up-to-date records of compound inventory, including quantities, locations, batch numbers and expiration dates.
• Monitor and report on stock levels to ensure an adequate supply for ongoing research and screening activities.
• Perform routine inspections to ensure the integrity and safety of stored compounds.

2. Compound Tracking and Documentation:

• Utilised laboratory information management systems (LIMS) and other digital tools to record, track and maintain compound data.
• Generate and update compound inventory reports, including batch information, chemical properties, and associated documentation.
• Prepare, maintain and ensure accessibility of safety data sheets (SDS) for all compounds, adhering to regulatory requirements.

 3.  Automation & System Integration:

• Implement, operate, and oversee automated liquid-handling and compound-dispensing systems to enhance efficiency, accuracy, and throughput.
• Collaborate with automation engineers and IT specialists to integrate robotic workflows, scheduling software, and compound databases into unified digital ecosystems.
• Support the development of automated data pipelines to improve sample traceability, compound-to-screen data linkage, and machine learning readiness.

4. Collaboration and Support:

• Work closely with medicinal chemists, screening teams, and informatics groups to ensure compound availability, integrity, and traceability.
• Receive and process compound requests from research teams, ensuring accuracy and compliance with company procedures.
• Prepare compounds for distribution, including labeling, packaging, and documentation.
• Maintain a log of compound distributions and returns.

5. Safety and Compliance:

• Adhere to safety protocols and guidelines for handling, storing, and disposing of chemical compounds.
• Ensure compliance with institutional and external regulations governing hazardous material management.
• Promote a culture of safety and accountability by routinely reviewing and updating chemical safety practices

6. Communication:

• Serve as a key liaison with researchers, scientists, and other stakeholders to align compound management activities with project priorities.
• Communicate effectively across team members and departments to coordinate compound management activities and address any issues or concerns.

7. Continuous Improvement & Innovation:

• Identify opportunities to optimize compound management processes, reduce waste, and enhance efficiency.
• Recommend and implement enhancements in inventory management systems and workflows.
• #Support data harmonization efforts and contribute to building a machine learning ready infrastructure connecting compound, assay and screening dataset.

8.  Training and Development:

• Stay current with developments in compound management best practices and technologies.
• Provide training and guidance to colleagues and new team members, as needed.

General Requirements

• Bachelor’s or Masters Degree in biological sciences, chemistry, engineering sciences or computer science.
• At least 2 years academic or industrial experience in biology or chemistry laboratories as a technician or research officer. 
• Strong organisational and communication skills, demonstrated ability in establishing and managing research partnerships.
• Ability to work independently and as part of a team in a fast-paced, dynamic environment
• Willingness to learn new techniques and adapt to changing priorities

Preferred Skills/Experiences:

• Experience in lab automation and liquid handling platforms.
• Experience with inventory management of samples or compounds, database software.
• Familiarity with robotics integration or lab digitalization initiatives.
• Strong understanding of chemical data formats (SMILES, SDF, CSV) and integration with cheminformatics tools.
• Knowledge and experience of the process of performing high throughput screening assays using microplates.

Job Description

We are looking for a passionate and capable individual to work with flexible sensors, wearable technologies, and benchtop biochemical analytics.

1. Be familiar with electrochemistry and electrochemical detection/analytics, colorimetric assays, enzymatic reactions, and biochemistry.
2. Be familiar with, and regular/daily wet-lab processes, materials processing, sample preparation, and electrochemical device preparation.
3. Be familiar with device and materials characterisation, such as common electrochemical approaches (CV, amperometry, DPV, SWV, etc), impedance measurements, basic optical measurements, and standard microscopy.
4. Possess basic computational abilities such as python, basic AI skills, with a keen eye for automation.
5. Be highly motivated for intellectual output (problem solving, publications, IP and general knowledge creation), able to learn quick on the job, able to think outside the box for research and engineering solutions

Qualifications & Field of Study:

Bachelors in preferably biomedical engineering, or materials science and engineering; chemical or electronics engineering or related fields are also relevant.

1. Good understanding of sensing materials, conductive/semiconductive materials, electronic devices, electrochemical sensors, and their related device engineering/development and characterisation tools
2. Good with detailed hands-on work in wet lab, meticulous and attention to detail; good with characterisation measurements
3. Have sufficient computational knowledge and abilities to complement research, including basic programming language, basic AI skills, awareness of automation etc.
4. Basic awareness and knowledge of biosensors, wearables technology, healthcare/medtech landscape.

Other Requirements:

1. Strongly driven for intellectual output and knowledge creation
2. Resourcefulness in problem solving
3. Diligent and team player, work in multi-disciplinary environments.

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.

Job Description

The project is related to exploration and application of artificial intelligence (AI) in design, analysis, discovery and validation of new ferroelectric and piezoelectric material for high-performance energy conversion or signal transmission functions. The materials particularly include ferroelectric and piezoelectric single crystals and thin films as demanded for producing competitive MEMES devices and ultrasonic transducers. The job scope covers design, growth, evaluation and analysis of ferroelectric and piezoelectric materials and related database generation for AI implementation, and relevant validation and demonstration.

Requirements:
• Ph.D in physics, material science, engineering; or a bachelor/master degree holder with expertise and skills related to data science (Scientist or Engineer position)
• Passion in creating new ferroelectric and piezoelectric materials, or application of AI in analyzing and discovering ferroelectric and piezoelectric materials.
• Any of R&D experience below: ferroelectric and piezoelectric characterization and analysis; data science, machine learning for design and validation of new materials; growth of piezoelectric single crystal; solid-state crystal growth; fabrication of ferroelectric thin films and ceramics.
• Good track record in technical publication, high performance record in university, or verifiable experience in the relevant areas as stated above.

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.

Job Description

The AI Research Scientist will contribute to clinical foundation model workstream for primary-care decision support. The role will focus on adapting open and/or institutionally approved foundation models to Singapore primary-care use cases, such as hypertension and cardiometabolic-renal multimorbidity scenarios involving diabetes, dyslipidaemia, CKD risk, medication burden, preventive care and follow-up planning.

The scientist will prepare structured training and evaluation data from clinical vignettes, synthetic cases, guideline-grounded Q&A, and eHINTS-like longitudinal data extracts where available. The role will support supervised fine-tuning, reinforcement learning or preference alignment experiments, and model evaluation against clinical templates, guideline compliance, safety constraints and usability requirements.

Key Responsibilities

• Prepare model-ready datasets from clinical vignettes, synthetic consultation cases, longitudinal records and guideline-derived tasks.
• Develop and run fine-tuning, instruction-tuning, preference-alignment and/or retrieval-augmented generation experiments for GP-oriented clinical tasks.
• Implement evaluation scripts for guideline adherence, factuality, safety alerts, medication recommendations, missing-data handling and structured output quality.
• Support multimodal and longitudinal data modelling where patient histories, lab trends, medications, notes and care plans need to be represented over time.
• Work with clinical collaborators to translate hypertension and multimorbidity requirements into model tasks, prompts, labels and acceptance criteria.
• Document experiments, datasets, model cards, limitations and reproducibility steps for internal review.

Required Qualifications and Skills

• PhD Degree in computer science, AI, biomedical informatics, computational science, data science or a related quantitative field.
• Hands-on experience with Python and modern deep-learning frameworks such as PyTorch, Hugging Face Transformers, vLLM or equivalent.
• Working knowledge of LLM fine-tuning, prompt engineering, retrieval-augmented generation, evaluation pipelines and reproducible ML experimentation.
• Ability to process structured and unstructured clinical data safely, including tabular records, notes, medications, lab values and guideline documents.
• Good understanding of model evaluation, error analysis, data quality control and responsible AI practices in healthcare or other high-stakes domains.

Preferred Experience

• Experience with clinical NLP, medical LLMs, healthcare datasets, FHIR/EMR-style data, or guideline-based decision support.
• Experience building synthetic data, simulation-based cases, or benchmark datasets for healthcare AI.
• Familiarity with primary-care chronic disease management, especially hypertension, diabetes, lipids, CKD risk and medication safety.
• Experience with GPU-based model training, experiment tracking, and deployment-oriented inference optimization. 

Job Summary

About Us

At the Institute of High Performance Computing (IHPC), A*STAR, we drive innovation at the intersection of artificial intelligence and healthcare. Our mission is to build large language models (LLMs), agentic AI and multimodal foundation models that can transform clinical decision support, biomedical discovery, and public health. We are looking for AI (Senior)Scientist strong applied AI skills ready to build large-scale systems, and you will contribute to innovations that make real impact in healthcare.

Key Responsibilities

• Research & DevelopmentDevelop novel architectures, training strategies, and optimization methods for LLMs, agentic AI, vision foundation model and multimodal foundation models.Advance instruction tuning, reinforcement learning (RLHF/GRPO), retrieval-augmented generation (RAG), and knowledge-grounded reasoning in medical AI.Design and implement multimodal learning pipelines that integrate text, imaging, omics, and real-world clinical data.
• Translation & CollaborationPrototype AI systems for clinical and biomedical applications (e.g., decision support, conversational AI, population health, drug discovery).Benchmark models against state-of-the-art healthcare AI datasets and evaluation frameworks.Collaborate with industry and healthcare partners to enable translation, licensing, and commercialization.
• Scientific LeadershipPublish in top-tier AI/ML venues (e.g., NeurIPS, ICML, ICLR, AAAI, ACL) and high-impact biomedical journals (e.g., Nature Medicine).Contribute to open science initiatives (datasets, model releases, benchmarks).Secure funding through collaborative research proposals with academia, healthcare institutions, and industry.

Qualifications

Minimum Qualifications

• PhD in Computer Science, Artificial Intelligence, Machine Learning, or related fields.
• Strong publication record in top AI/ML venues (e.g., NeurIPS, ICML, ICLR, ACL) or high-impact biomedical journals.
• Deep expertise in LLMs, vision foundation models, or multimodal AI.
• Strong skills in deep learning frameworks (PyTorch, TensorFlow, JAX) and distributed/HPC training.

Preferred Qualifications

• Experience in large-scale LLM and/or foundation model training and deployment.
• Experience with medical or biomedical data (EHR, clinical notes, imaging, genomics).
• Familiarity with biomedical ontologies and knowledge graphs (UMLS, SNOMED CT, PubMed).
• Understanding of AI ethics, safety, and regulatory considerations in healthcare.

What We Offer

• Opportunity to push the frontiers of AI research while delivering real-world healthcare impact.
• A multidisciplinary environment with leading AI scientists, clinicians, and industry partners.
• Access to large-scale compute resources and unique biomedical datasets.
• Support for publications, conference participation, and translational pathways including licensing and spin-offs.

Job Summary

About the Role

The Institute of High Performance Computing (IHPC), A*STAR, is seeking a highly motivated Senior Research Scientist to conduct cutting-edge research in Artificial Intelligence and Machine Learning, with a focus on advancing AI-driven scientific discovery across healthcare, life sciences, biology, and biomedical research.

The successful candidate will lead the development of next-generation AI technologies, including foundation models, multimodal learning systems, scientific machine learning, generative AI, and agentic AI systems that accelerate scientific discovery and translate research innovations into real-world impact.

Key Responsibilities

Research & Innovation

• Develop AI models and platforms that accelerate discovery in healthcare, life sciences, and biomedical research.
• Advance foundation models that learn from large-scale biological, clinical, molecular, and scientific datasets.
• Develop AI systems for:
• Multi-omics analysis
• Drug discovery and therapeutic development
• Precision medicine
• Biomarker discovery
• Disease prediction and prognosis
• Scientific knowledge extraction and reasoning
• Build agentic AI systems capable of hypothesis generation, experiment design, scientific reasoning, and autonomous discovery.
• Develop methodologies that integrate experimental data, simulations, scientific literature, and domain knowledge to support scientific decision-making and discovery.

• Collaborate with clinicians, biologists, healthcare researchers, and domain scientists to translate AI innovations into real-world applications.
• Drive the development of reusable AI platforms, foundation models, and scientific discovery systems.
• Contribute to technology transfer, intellectual property generation, and commercialization opportunities.
• Lead collaborations with academic institutions, healthcare organizations, government agencies, and industry partners.

Scientific Leadership

• Publish high-impact research in leading AI, machine learning, healthcare, and scientific journals and conferences.
• Contribute to grant proposals, project planning, and strategic research initiatives.
• Mentor junior researchers, engineers, and students.
• Represent IHPC in collaborations with academic, healthcare, government, and industry partners.

Requirements

Essential

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Computational Biology, Biomedical Engineering, Computer Engineering, or a related discipline.
• Strong track record in AI/ML research demonstrated through publications, patents, or impactful projects.
• Strong programming skills in Python and modern machine learning frameworks such as PyTorch or TensorFlow.
• Experience developing and evaluating machine learning and deep learning models.
• Experience working with large-scale datasets and computational infrastructure.
• Strong interest in applying AI to scientific discovery, healthcare, and life science challenges.

Preferred

• Experience in one or more of the following areas:Foundation Models for ScienceComputational Biology and Multi-OmicsDrug Discovery and Molecular ModelingBiomedical AIPrecision MedicineScientific Knowledge GraphsScientific Reasoning and Agentic AI SystemsHealthcare AI and Clinical Decision SupportGenerative AI for Scientific Discovery

What We Offer

• Opportunity to work on nationally significant AI for Science, Healthcare, and Life Sciences initiatives.
• Access to world-class computational infrastructure, large-scale scientific datasets, and advanced research facilities.
• Collaboration with leading AI researchers, clinicians, scientists, and industry partners.
• A dynamic environment supporting both fundamental AI research and translational impact.
• Opportunities to shape the future of AI-driven scientific discovery and healthcare innovation.

Job Summary

Role Overview

You will lead the institute’s efforts to identify emerging technology trends, market opportunities, and ecosystem shifts. In this role, you will oversee technology and market intelligence, assess the institute’s strengths against external opportunities, and shape clear recommendations on where to build, partner, or step back.

Key Responsibilities

• Oversee market and technology sensing to identify emerging trends, industry shifts, policy changes, and partnership opportunities.
• Lead technology intelligence — assessing emerging scientific areas, technical trajectories, maturity, standards, and competitive activity.
• Lead market intelligence — assessing industry needs, adoption barriers, value pools, investment trends, and partnership opportunities.
• Map the institute’s research strengths, platforms, talent, and partnerships against emerging opportunities.
• Develop clear recommendations on where to build, deepen, partner, or deprioritise capabilities.
• Build and lead a high-performance, engaged, multi-disciplinary team.

Requirements

• Advanced degree in science, engineering, or a related field. Postgraduate training is advantageous.
• Strong experience in market intelligence, technology intelligence, technology strategy, foresight, consulting, or innovation management.
• Ability to assess technology maturity, market opportunities, industry demand, competitive activity, and ecosystem developments.
• Strong analytical and communication skills, with the ability to turn intelligence into actionable strategic recommendations.
• High proficiency with Generative AI tools will be an advantage.

Career Growth & Impact

• Be the first to see what’s next. You will lead intelligence efforts across emerging technologies — from generative AI to quantum computing and green energy — with direct access to world-class researchers and labs.
• Build an unrivalled professional network. You will engage regularly with industry leaders, startups, government agencies, and international research partners.
• Turn insights into action. Your recommendations will directly determine where the organisation builds, partners, or steps back — a rare level of strategic influence for an intelligence role.
• Open doors across industries. This role is a springboard into technology strategy, corporate development, venture capital, or innovation policy.

Job Summary

The Institute of High Performance Computing (IHPC), A*STAR, was established in April 1998 to provide leadership in high performance computing as a strategic resource for scientific inquiry and industry development. Our mission is to advance science and technology, and develop leading-edge applications through high performance computing and computational science. We have long-term ties with industry partners, including multinational companies and local SMEs, which ensures that our R&D activities stay focused and relevant to real-world needs. We also have active cooperation with the world’s top academics and academic institutions.

We are looking for a motivated and versatile individual to join the Healthcare team. The role will support the development, adoption, and continuous improvement of reusable AI assets and platforms through ecosystem engagement, platform operations, product thinking and practical UI/UX capability.

Research Engineer (Reusable Healthcare AI Assets)

The successful candidate will work closely with researchers, engineers, product owners, healthcare and public-sector stakeholders, and industry partners to identify user needs, translate them into actionable platform requirements, and drive the adoption of reusable AI assets. The role is suitable for someone who can engage stakeholders effectively, structure feedback into product and operational priorities, and contribute to simple, intuitive user journeys, wireframes, prototypes, dashboards, and documentation for AI platforms.

Requirements

• Experience in at least one of the following areas: AI/ML platform delivery, product or platform operations, technical project management, ecosystem or stakeholder engagement, developer relations, digital transformation, UI/UX design, or technology adoption.
• Working understanding of AI/ML systems, data-driven applications, software platforms, APIs, cloud environments, MLOps, or reusable software/assets. Deep research specialisation is not required, but the candidate must be comfortable working with technical teams.
• Ability to translate between domain needs, user pain points, operational constraints, and technical implementation requirements.
• Practical exposure to user research, journey mapping, wireframing, prototyping, usability testing, information architecture, or interface review.
• Strong written and verbal communication skills, with the ability to explain technical capabilities and trade-offs to both technical and non-technical audiences.
• Good planning, coordination, and stakeholder management skills, with the ability to manage multiple workstreams independently in a fast-moving environment.

Preferred qualifications (one or more of the following)

• Experience in healthcare, biomedical, public-sector, or regulated digital systems.
• Hands-on experience with UI/UX or prototyping tools such as Figma, Miro, FigJam, Balsamiq, or equivalent.
• Ability to build lightweight prototypes, demos, or dashboards using tools such as React, JavaScript/TypeScript, HTML/CSS, Streamlit, Gradio, Dash, Tableau, Power BI, or similar.
• Experience managing reusable asset catalogues, platform onboarding journeys, technical documentation portals, design systems, knowledge bases, or developer-facing resources.
• Familiarity with agile delivery and collaboration tools such as Jira, Confluence, Git, GitHub/GitLab, or equivalent.
• Awareness of responsible AI, model evaluation, AI safety, data privacy, cybersecurity, and governance considerations for AI systems.

Interested applicants should submit their curriculum vitae, together with a short cover note describing relevant experience in ecosystem engagement, platform operations, AI/ML systems, and UI/UX or product-related work. The level of appointment will be commensurate with experience.

For applicants, please send your curriculum vitae to Dr Ricardo Shirota Filho (ricardo_shirota_filho@a-star.edu.sg)

Job Summary

Role Overview

You will help leadership build and manage a balanced research portfolio — spanning themes, maturity levels, risk profiles, funding sources, and paths to real-world impact. You will develop investment cases, lead resource planning, and ensure that the institute’s research bets are strategically sound.

Key Responsibilities

• Support long-term research portfolio planning across themes, maturity levels, risk profiles, funding sources, and paths to impact.
• Develop investment cases and decision papers to support leadership discussions on major research bets and capability-building.
• Evaluate programmes based on scientific excellence, strategic relevance, and potential for real-world impact.
• Lead long-term planning for budget, headcount, infrastructure, compute, data, and platforms to support the institute’s goals.
• Partner with finance, HR, operations, IT, and research teams to align resource planning with strategic priorities.

Requirements

• Degree in science, engineering, business, finance, operations, or a related field; experience in R&D portfolio planning or resource management is advantageous.
• Strong understanding of research portfolio management, resource planning, budgeting, headcount planning, and programme evaluation.
• Ability to develop investment cases, decision papers, portfolio analyses, and resource plans for senior leadership.
• Strong cross-functional coordination skills, with experience working across research, finance, HR, operations, and IT teams.

Career Growth & Impact

• Manage a portfolio at national scale. You will oversee research investments spanning multiple domains, risk profiles, and funding sources — the kind of breadth usually found only at global R&D organisations.
• Influence major investment decisions. Your analysis and recommendations will directly shape which research bets the institute makes — and where it builds new capabilities.
• Build a versatile, cross-functional skill set. You will work at the intersection of science, finance, operations, HR, and IT — experience that is highly transferable across sectors.
• Accelerate your career. A strong foundation for progression into senior research management, chief-of-staff roles, or leadership positions in national research planning.
• on management.

Job Summary

Role Overview

You will partner with senior leadership to shape, execute, and communicate the institute’s strategic direction. Reporting to Senior Director, Strategy, you will play a central role in strategic planning, research portfolio development, and market and technology sensing — translating big-picture priorities into actionable plans that drive real outcomes.

Key Responsibilities

• Develop the institute’s overall strategy, including vision, priorities, research focus areas, and long-term growth plans.
• Lead the creation and refresh of strategy documents, annual workplans, research roadmaps, and implementation plans.
• Translate strategic priorities into programmes, milestones, KPIs, resource plans, and cross-functional workstreams.
• Oversee the planning cycle, including leadership offsites, strategy retreats, and annual planning sessions.
• Engage internal and external stakeholders to drive strategic alignment and collaboration.
• Build and lead a high-performance, engaged, multi-disciplinary team.

Requirements

• Advanced degree in science, engineering, technology, business, public policy, or a related field; PhD, MBA, or equivalent experience is advantageous.
• Significant experience in strategy, corporate planning, research management, consulting, or public-sector planning.
• Strong ability to translate complex scientific, organisational, and policy issues into clear priorities, workplans, and executive recommendations.
• Excellent stakeholder management and communication skills, with experience engaging senior leaders, research teams, and external partners.

Career Growth & Impact

• Shape national R&D priorities. You will directly influence how one of Asia’s leading public research organisations invests in science and technology — from AI and sustainability to advanced manufacturing.
• Work at the leadership table. You will partner with institute directors, government agencies, and ecosystem leaders, building a high-level network across Singapore’s innovation landscape.
• See your strategy come to life. Unlike advisory roles, you will own the end-to-end journey from strategy formulation to execution — roadmaps, KPIs, resource plans, and cross-team delivery.
• Grow into senior leadership. This role is a launchpad into senior R&D leadership, national science policy, or C-suite strategy positions.

Job Summary

Role Overview

You will partner with senior leadership to shape, execute, and communicate the institute’s strategic direction. Reporting to Senior Director, Strategy, you will play a central role in strategic planning, research portfolio development, and market and technology sensing — translating big-picture priorities into actionable plans that drive real outcomes.

Key Responsibilities

• Develop the institute’s overall strategy, including vision, priorities, research focus areas, and long-term growth plans.
• Lead the creation and refresh of strategy documents, annual workplans, research roadmaps, and implementation plans.
• Translate strategic priorities into programmes, milestones, KPIs, resource plans, and cross-functional workstreams.
• Oversee the planning cycle, including leadership offsites, strategy retreats, and annual planning sessions.
• Engage internal and external stakeholders to drive strategic alignment and collaboration.
• Build and lead a high-performance, engaged, multi-disciplinary team.

Requirements

• Advanced degree in science, engineering, technology, business, public policy, or a related field; PhD, MBA, or equivalent experience is advantageous.
• Significant experience in strategy, corporate planning, research management, consulting, or public-sector planning.
• Strong ability to translate complex scientific, organisational, and policy issues into clear priorities, workplans, and executive recommendations.
• Excellent stakeholder management and communication skills, with experience engaging senior leaders, research teams, and external partners.

Career Growth & Impact

• Shape national R&D priorities. You will directly influence how one of Asia’s leading public research organisations invests in science and technology — from AI and sustainability to advanced manufacturing.
• Work at the leadership table. You will partner with institute directors, government agencies, and ecosystem leaders, building a high-level network across Singapore’s innovation landscape.
• See your strategy come to life. Unlike advisory roles, you will own the end-to-end journey from strategy formulation to execution — roadmaps, KPIs, resource plans, and cross-team delivery.
• Grow into senior leadership. This role is a launchpad into senior R&D leadership, national science policy, or C-suite strategy positions.

Job Summary

About the Role

The Institute of High Performance Computing (IHPC), A*STAR, is seeking an outstanding Senior Research Scientist to lead cutting-edge research in Artificial Intelligence, Computer Vision, Vision-Language Models (VLMs), Multimodal AI, and Agentic AI Systems.

The successful candidate will drive the development of next-generation AI technologies for healthcare, biomedical, and scientific applications, translating fundamental AI advances into impactful real-world solutions.

Key Responsibilities

Research & Innovation

• Lead and conduct high-impact research in Artificial Intelligence, Machine Learning, and Computer Vision.
• Develop novel algorithms and models in areas such as:
• Multimodal Learning
• Foundation Models
• Generative AI and Large Language Models
• Computer Vision
• Agentic AI Systems
• Design scalable AI systems capable of integrating heterogeneous data sources, including imaging, sensor, text, and clinical data.
• Develop methodologies for prediction, reasoning, decision support, and knowledge discovery.

Translational AI

• Drive the development of reusable AI platforms, foundation models, and intelligent agent systems.
• Translate AI innovations into healthcare, biomedical, and scientific applications.
•  Lead collaborations with clinicians, scientists, academic institutions, government agencies, and industry partners.
• Contribute to technology transfer, intellectual property generation, and commercialization opportunities.

Scientific Leadership

• Publish high-quality research in leading AI, machine learning, and application-domain conferences and journals.
• Contribute to grant proposals, project planning, and intellectual property development.
• Mentor junior researchers, engineers, and students.
• Represent IHPC in collaborations with academic, clinical, government, and industry partners.

Requirements

Essential

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, Biomedical Engineering, or a related discipline.
• Strong track record in AI/ML research demonstrated through publications, patents, or impactful projects.
• Strong programming skills in Python and modern machine learning frameworks such as PyTorch or TensorFlow.
• Experience developing and evaluating machine learning and deep learning models.

What We Offer

• Opportunity to work on nationally significant AI initiatives.
• Access to world-class computational infrastructure and research facilities.
• Collaboration with leading researchers, clinicians, scientists, and industry partners.
• A dynamic environment supporting both fundamental AI research and real-world translation.

Job Summary

Job Purpose

The Knowledge Engineer will be responsible for designing, constructing, and maintaining knowledge graphs derived from heterogeneous enterprise documents. The role involves leveraging Large Language Models (LLMs) for knowledge extraction, ontology-driven structuring, and question answering over knowledge graphs to support intelligent search, reasoning, and decision-making systems.

Key Responsibilities

• Leverage LLMs to extract structured knowledge (entities, relations, attributes) from unstructured and semi-structured documents such as:Maintenance manualsProduct design documentsTroubleshooting guidesLessons learned reports
• Process documents in multiple formats, including Word, PDF, PowerPoint, and Excel.
• Design, construct, and maintain knowledge graphs, including:Schema and ontology designEntity and relationship modellingData normalisation and validation
• Implement and manage knowledge graph storage using graph databases such as Neo4j and GraphDB.
• Develop LLM-powered question answering and interaction pipelines over knowledge graphs, enabling:Natural language queriesContext-aware and explainable responses grounded in structured knowledge
• Collaborate with domain experts and stakeholders to refine ontologies, extraction logic, and use cases.

Required Skills & Experience

• Strong understanding of ontology design, knowledge graph modeling, and semantic data representation.
• Proficiency in Python, with experience building data processing and NLP pipelines.
• Solid understanding of prompt engineering and LLM-based workflows.
• Hands-on experience working with LLMs, including both:Closed-source models (e.g., GPT-based APIs)Open-source models (e.g., LLaMA, Qwen, etc.)
• Experience with graph databases, particularly Neo4j and/or GraphDB.

Preferred / Advantageous Skills

• Experience in information extraction, document understanding, or NLP pipelines.
• Familiarity with RDF, OWL, SPARQL, or Cypher is a plus.
• Experience integrating LLMs with structured knowledge sources (e.g., KG-augmented QA, RAG with graphs).

Key Competencies & Attributes

• Strong analytical and problem-solving skills, with the ability to translate unstructured information into well-defined data models.
• Ability to work independently while collaborating effectively within a multidisciplinary team.
• Good communication skills to engage with technical and non-technical stakeholders.
• Demonstrated willingness to continuously learn and keep up with advances in LLMs, NLP, and knowledge engineering.

Key Responsibilities

• Develop data-driven energy disaggregation models to estimate machine-, process-, and batch-level energy consumption from aggregated or limited metering data.
• Design and implement energy monitoring, analytics and benchmarking algorithms for energy performance tracking, anomaly detection, and causal analytics related to energy-saving of industrial equipment and manufacturing processes.
• Conduct experiments, model validation, and performance evaluation using industrial datasets.
• Work closely with project partners, engineers, and researchers to translate research outcomes into deployable industrial solutions.

Requirements

• Bachelor’s or Master’s degree in Electrical Engineering, Mechanical Engineering, Computer Science, Data Science, Industrial Engineering, or a related field.
• Strong programming skills in Python, with experience in data analytics, machine learning, and time-series processing.
• Knowledge of energy systems, power consumption analysis, industrial equipment, or manufacturing processes.
• Experience with machine learning techniques for regression, classification, anomaly detection, forecasting, or signal disaggregation.
• Ability to process and analyze large-scale time-series datasets.
• Good problem-solving skills and ability to work independently in applied research and development projects.
• Good written and verbal communication skills.

Preferred Qualifications

• Experience in non-intrusive load monitoring, energy disaggregation, virtual sensing, or industrial energy analytics.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.
• Experience with causal analytics.
• Knowledge of manufacturing systems, additive manufacturing, CNC, heat treatment, pumps, compressors, motors, or other industrial equipment.
• Prior experience in applied R&D projects with industry partners is an advantage.

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.

Job Description

The Senior AI Research Scientist will be working on clinical multi-agent CDS engineering workstream. The role will design and implement the MAS harness that coordinates GP, pharmacist, specialist, guideline/evidence, medication-safety and workflow agents for primary-care decision support. The system should support pre-consult briefs, iterative re-inference during consultation, safety checks, and structured next-best-action recommendations.

The scientist will be responsible for translating clinical workflow requirements into an executable architecture: agent contracts, orchestration logic, memory/state management, tool interfaces, retrieval layers, evaluation harnesses and observability. The role will also lead simulation-based testing and validation using clinical vignettes, synthetic cases, public benchmarks and protected clinical data pathways where approved.

Key Responsibilities

• Design and implement the MAS/CDS harness, including agent roles, orchestration policies, memory/state handling, tool calling, guardrails and error recovery.
• Build simulation-based evaluation workflows that generate cases, run multi-agent consultations, compare outputs with labels or clinician review, and record failure modes.
• Engineer validation pipelines for guideline compliance, medication safety, role adherence, hallucination detection, uncertainty handling, and workflow usability.
• Integrate clinical foundation models, retrieval components, guideline knowledge bases, structured patient data and clinician feedback loops into a coherent CDS prototype.
• Lead technical design for pre-consult briefs and iterative consultation support, including re-inference when new patient information, lab results or clinician inputs are added.
• Collaborate with clinicians, product/workflow teams and evaluation teams to define acceptance criteria, benchmark scenarios, safety thresholds and pilot-readiness evidence.
• Mentor junior researchers/engineers and establish engineering standards for reproducible MAS experiments, audit trails, dataset versioning and model/system documentation.

Required Qualifications and Skills

• PhD degree in AI, computer science, machine learning, biomedical informatics, computational science or a related field.
• Strong hands-on experience building LLM applications, agentic systems, orchestration frameworks, evaluation harnesses or production-grade AI research prototypes.
• Deep understanding of LLM evaluation, retrieval-augmented generation, tool use, safety guardrails, observability, state management and experiment reproducibility.
• Ability to design validation approaches for clinical AI systems, including synthetic and real-world data evaluation, clinician review workflows and error analysis.
• Strong software engineering skills in Python and modern AI system stacks; able to convert research ideas into maintainable prototypes and reusable platforms.

Preferred Experience

• Experience with clinical decision support systems, medical LLMs, healthcare workflow integration, FHIR/EMR/eHINTS-like data pathways or regulated AI evaluation.
• Experience with multi-agent frameworks, simulation environments, LLM-as-judge systems, benchmark construction, or safety testing for high-stakes AI.
• Knowledge of primary-care chronic disease management and clinical safety issues such as polypharmacy, contraindications, formulary constraints and care-gap detection.
• Track record leading small technical teams, mentoring junior researchers, and coordinating with clinical, product and governance stakeholders.

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.

Job Summary

About the Role

The Institute of High Performance Computing (IHPC), A*STAR, is seeking a highly motivated Research Scientist to conduct cutting-edge research in Healthcare AI Safety, Trustworthy AI, and Responsible AI Systems.

The successful candidate will lead the development of methodologies, frameworks, and technologies that ensure AI systems are safe, reliable, robust, transparent, and clinically trustworthy for deployment in healthcare settings. The role will focus on advancing AI safety research while enabling the responsible translation of AI innovations into clinical practice and healthcare operations.

Key Responsibilities

Research & Innovation

• Conduct original research in Healthcare AI Safety, Trustworthy AI, Machine Learning, and Artificial Intelligence.
• Develop novel methodologies and frameworks in areas such as:
• AI Safety and Alignment
• Trustworthy and Responsible AI
• Explainable and Interpretable AI
• AI Evaluation and Benchmarking
• Robustness and Reliability
• Human-AI Collaboration
• AI Governance and Risk Management
• Design techniques for detecting, mitigating, and monitoring AI failures, biases, hallucinations, and unsafe behaviors.
• Develop methods for uncertainty quantification, confidence estimation, and risk-aware decision-making.

• Develop safety frameworks for foundation models, large language models, multimodal AI systems, and agentic AI systems used in healthcare.
• Design methodologies to evaluate clinical safety, reliability, fairness, and generalizability of AI systems across diverse patient populations and healthcare settings.
• Develop monitoring systems for post-deployment surveillance, model drift detection, and continuous safety assessment.
• Build mechanisms for human oversight, escalation, and safe human-AI collaboration in clinical workflows.
• Develop evaluation frameworks for clinical decision support systems, healthcare copilots, and autonomous healthcare agents.
• Advance approaches for safeguarding patient privacy, data security, and responsible use of healthcare data.

Translational AI Safety

• Collaborate with clinicians, healthcare providers, regulators, policymakers, and industry partners to support safe deployment of AI systems.
• Contribute to healthcare AI governance frameworks, safety standards, regulatory science, and best practices.
• Translate AI safety research into practical tools, platforms, and operational frameworks for healthcare organizations.
• Support technology transfer, intellectual property generation, and commercialization opportunities.

Scientific Leadership

• Publish high-impact research in leading AI, machine learning, healthcare, and AI safety conferences and journals.
• Contribute to grant proposals, project planning, and strategic research initiatives.
• Mentor junior researchers, engineers, and students.
• Represent IHPC in collaborations with healthcare institutions, government agencies, regulators, and industry partners.

Requirements

Essential

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Biomedical Informatics, Healthcare Informatics, or a related discipline.
• Strong track record in AI/ML research demonstrated through publications, patents, or impactful projects.
• Strong programming skills in Python and modern machine learning frameworks such as PyTorch or TensorFlow.
• Experience developing and evaluating machine learning and deep learning models.
• Strong interest in AI safety, responsible AI, healthcare applications, and trustworthy AI systems.

Preferred

• Experience in one or more of the following areas:
• AI Safety and Alignment
• Trustworthy and Responsible AI
• Explainable AI (XAI)
• Foundation Models and Large Language Models
• Agentic AI Systems
• Healthcare AI and Clinical Decision Support
• AI Evaluation and Benchmarking
• Human Factors and Human-AI Interaction
• Regulatory Science and AI Governance
• Healthcare Data Privacy and Security

What We Offer

• Opportunity to shape the future of safe, trustworthy, and responsible AI in healthcare.
• Access to world-class computational infrastructure, healthcare datasets, and research facilities.
• Collaboration with leading AI researchers, clinicians, healthcare providers, regulators, and industry partners.
• A dynamic environment supporting both fundamental AI safety research and real-world deployment.
• Opportunities to influence national and international healthcare AI safety standards and frameworks