Total 483 Science / R&D / Research job vacancies in BUKIT PASIR

Job Summary

About the Role

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

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

Key Responsibilities

AI System Development

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

Research Translation

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

Software & Infrastructure Engineering

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

Deployment & Integration

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

Requirements

Essential

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

Preferred

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

What We Offer

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

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

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

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

Main Responsibilities

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

Job Requirements

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

We regret that only shortlisted candidates will be notified.

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

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-%28Biological-Sciences%29/33316-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Molecular Breeding Laboratory at the Lee Hiok Kwee Functional Genomics Laboratories, Department of Biological Sciences led by Associate Professor Chew Fook Tim, is currently looking for TWO Research Fellows with relevant PhDs, and TWO Research Assistants with BSc(Hons) degree or MSc in relevant fields and background, to join the project on the Molecular Breeding of Leafy Greens and Fruiting Vegetables / Seed Innovation Hub.

The work would include:

• Large-scale Global Germplasm Evaluation and Assessment,
• Key Deep Phenotypic Definition and Evaluation, including molecular, cell culture-based and biochemical bioassays,
• Characterization of Genetic Control, Genome-wide Associations, and Functional Characterization of Candidates,
• Crossing, Cultivar and Lines Development,
• Integration of Genomic Data into Cultivation Processes,
• Multi-Location Trial Evaluations, 
• Project Management of External Collaborations, and
• Scientific Communications and Publications.

Qualifications

PhD Degree in Science and in related fields.

Skills:

• Strong motivation and leadership in pursuing challenging scientific questions.
• An ability to work well with interdisciplinary colleagues.
• Experience in mentoring and training junior researchers (including undergraduates and polytechnic interns).
• Excellent written and interpersonal communication skills.
• Good time and resource management skills.

Experience:

• Experience in Bioinformatics / Genetics / Statistics is mandatory and should be able to code in R.
• In addition, experience in Plant Molecular Biology techniques including CRISPR and Functional Characterization of Genetic Control, Large Scale -omics Technologies, and Data Analysis, would be an advantage.

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

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

We regret that only shortlisted candidates will be notified.

Job Description

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

Purpose of the post

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

Main duties and responsibilities

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

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

Qualifications

The applicant should:

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

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

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

We regret that only shortlisted candidates will be notified.

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

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

We regret that only shortlisted candidates will be notified.

Job Description

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

Purpose of the post

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

Main duties and responsibilities

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

Qualifications

The applicant should:

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

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

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

We regret that only shortlisted candidates will be notified.

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Hybrid-organic-inorganic-perovskites%29/33365-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The team of Prof Loh Kian Ping invites applications for a Research Fellow position working in the synthesis and characterization of hybrid organic inorganic perovskites single crystal and thin film. Our research focuses on engineering chirality and functionality on hybrid superlattices.  

Candidates with the following experiences will be advantaged:

(1)    the solution phase synthesis of large sized 2D hybrid organic inorganic perovskites crystals
(2)    Design of chiral or multiferroic 2D hybrid organic inorganic perovskites
(3)    Adept with the use of piezoresponse force microscopy to study ferroelectric phases
(4)    Adept with optical spectroscopic methods to study excitonic processes
(5)    Ability to solve single crystal XRD 

The candidate should have a PhD degree and strong track record in Materials Chemistry or Physics, with publishing in related areas.

An attractive renumeration package will be offered for suitable candidate with a strong record in 2-D condensed matter physics and who has good publication record. 

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-%28Hybrid-organic-inorganic-perovskites%29/33368-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The team of Prof Loh Kian Ping invites applications for a Research Fellow position working in the synthesis and characterization of hybrid organic inorganic perovskites single crystal and thin film. Our research focuses on engineering chirality and functionality on hybrid superlattices.  

Candidates with the following experiences will be advantaged:

(1)    the solution phase synthesis of large sized 2D hybrid organic inorganic perovskites crystals
(2)    Design of chiral or multiferroic 2D hybrid organic inorganic perovskites
(3)    Adept with the use of piezoresponse force microscopy to study ferroelectric phases
(4)    Adept with optical spectroscopic methods to study excitonic processes
(5)    Ability to solve single crystal XRD 

The candidate should have a PhD degree and strong track record in Materials Chemistry or Physics, with publishing in related areas.

An attractive renumeration package will be offered for suitable candidate with a strong record in 2-D condensed matter physics and who has good publication record. 

Responsible for the design and delivery of DeltaV application system on site.

Participate in the development and implementation of Automation solutions in line with S88 standards for the plant.

Creates and maintains applications according to technical design and requirements.

Develop and/or review System Development Life Cycle (SDLC) deliverables, compliant with the site's standards. Determine the processes and data flow that supports the needs of the project.

Design & Develop plan for modifications to be made to the system through working with team in development of systems architecture, specifications, controls strategies, sequence of operations through all stages.

Requirements

Experience in a similar role, ideally in the Pharmaceutical and/or Biotechnology industry.

Emerson DeltaV DCS system experience and DeltaV Batch experience required

Experience in the Designing and commissioning of DeltaV DCS project for GMP manufacturing site.

Technical proficiency on controls systems including familiarity with control panels, networking, panel/field wiring and PLC control systems.

Through understanding of Batch s88 standards (CM, EM, Phases, Recipes, Units etc)

Familiarity with GAMP lifecycle and quality management processes employed in the pharmaceutical sector

Ability to work well in a team environment

Supervise and conduct system testing Factory Acceptance Test (FAT)

Excellent computer skills, proficient in the use of the following Microsoft tools: Excel, SharePoint, Word and PowerPoint.

Excellent communication and customer orientation skills

Good analytical & problem-solving skills

Ensure project Automation Strategy is followed.

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Assistant-%28Pharmacy-and-Pharmaceutical-Sciences%29/33367-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The successful candidate will work with Dr Boxiang Liu as a Research Assistant, supporting the research administration and laboratory operations of a computational and experimental genomics lab.

The main responsibilities of the position include:
• Developing a strong familiarity with the lab’s overall research direction, which underpins all other responsibilities
• Coordinating and scheduling of research meetings with the relevant collaborators and lab members
• Assisting with grant proposal writing, grant management, and grant reporting
• Training new staff on safety and assisting with the preparation of hiring and onboarding documents, SOP and safety documents
• Organising research meetings outside the regular lab setting
• Proofreading manuscripts
• Keeping abreast of the latest developments in the field and contributing to brainstorming on research projects and grant proposals
• Purchasing reagents and managing laboratory inventory
• Conduct molecular biology work as required, including cloning, cell culture, and gel electrophoresis

Qualifications / Discipline: 
• BS or MS degree in a relevant discipline (including life sciences, biology, pharmacy, bioinformatics, business administration, or a related field) 

Skills: 
• Molecular biology techniques, cloning, cell culture, gel electrophoresis
• Research Literacy and interest in genomics and related life sciences
• Detail-oriented and highly organised
• Strong note-taking and document management skills
• Excellent written and spoken English
• Proficient with common office software and research-related tools
• High standards of integrity in handling confidential information
• Self-motivated to learn and improve the operational standards of the lab

Experience: 
• Prior experience in research administration, grant management, or laboratory operations is preferred
• Wet-lab experience (in molecular biology, cloning, cell culture, gel electrophoresis) is an advantage 

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-%28On-Chip-Polarimeters%29/33370-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The team of Prof Loh Kian Ping is seeking a highly motivated Research Fellow to lead the development of a miniaturized, on-chip polarimeter based on chiral 2D Halide Organic-Inorganic Perovskites for full Stokes vector detection. The candidate will focus on optical simulation, cleanroom nanofabrication, device integration, optoelectronic testing, and machine learning-driven signal reconstruction. 

Note: This role focuses on device engineering and computation; independent material synthesis is not required. 

Key Responsibilities:
•    Design & Simulation: Model sub-wavelength polarization-selective metasurfaces using electromagnetic simulation tools (FDTD/FEM) to establish optoelectronic eigenvectors.
•    Nanofabrication: Fabricate multi-pixel sensor arrays and integrate pre-synthesized chiral 2D HOIP layers into metasurface architectures in a cleanroom environment.
•    Optoelectronic Characterization: Build and operate automated optical benches to test multi-pixel photocurrent responses under varied polarization states.
•    Data Analysis & ML: Develop Python/MATLAB machine learning algorithms to map photocurrents to full Stokes parameters, targeting a reconstruction error of \(<1\%\).

Required Qualifications:
•    Ph.D. in Electrical Engineering, Applied Physics, Materials Science, Optical Engineering, or a related field.
•    Strong background in nanophotonics, metasurfaces, and polarization optics (Stokes vectors).
•    Hands-on cleanroom fabrication experience (EBL, photolithography, thin-film deposition).

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Assistant%2C-School-of-Computing/33376-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The National University of Singapore invites applications for the position of Research Assistant in the Department of Computer Science, School of Computing (SoC). SoC is strongly committed to research excellence in all its dimensions: Searching for fundamental results and insights, developing novel computational solutions to a wide range of applications, building largescale experimental systems, developing theories and policies for effective management of information systems in organizations, and improving the well-being of society. We seek to play an active role both internationally and locally in the core and emerging areas of Computer Science and Information Systems.

Our research will focus on the design and implementation of next-generation AI accelerators, including the development of new architecture designs (dataflow designs), reuse patterns, caching and the development of the infrastructure of the system needed to support the acceleration of AI platforms.

The Research Assistant will be responsible for working closely with the Principal Investigator and lab members on one or more research projects. He/she should possess experience or interest in at least one of the following research areas:

• Artificial Intelligence and Machine Learning
• Hardware Design, Circuits and Systems
• Algorithms
• Programming Languages & Software Engineering

Only shortlisted candidates will be notified.

Job Requirements

• A Bachelor’s degree with Honours in a relevant area; and
• Experience in research

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

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

We regret that only shortlisted candidates will be notified.

Job Description

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

Main responsibilities:

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

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

Training provided:

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

Qualifications

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

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

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-%28On-Chip-Polarimeters%29/33369-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The team of Prof Loh Kian Ping is seeking a highly motivated Research Fellow to lead the development of a miniaturized, on-chip polarimeter based on chiral 2D Halide Organic-Inorganic Perovskites for full Stokes vector detection. The candidate will focus on optical simulation, cleanroom nanofabrication, device integration, optoelectronic testing, and machine learning-driven signal reconstruction. 

Note: This role focuses on device engineering and computation; independent material synthesis is not required. 

Key Responsibilities:
•    Design & Simulation: Model sub-wavelength polarization-selective metasurfaces using electromagnetic simulation tools (FDTD/FEM) to establish optoelectronic eigenvectors.
•    Nanofabrication: Fabricate multi-pixel sensor arrays and integrate pre-synthesized chiral 2D HOIP layers into metasurface architectures in a cleanroom environment.
•    Optoelectronic Characterization: Build and operate automated optical benches to test multi-pixel photocurrent responses under varied polarization states.
•    Data Analysis & ML: Develop Python/MATLAB machine learning algorithms to map photocurrents to full Stokes parameters, targeting a reconstruction error of \(<1\%\).

Required Qualifications:
•    Ph.D. in Electrical Engineering, Applied Physics, Materials Science, Optical Engineering, or a related field.
•    Strong background in nanophotonics, metasurfaces, and polarization optics (Stokes vectors).
•    Hands-on cleanroom fabrication experience (EBL, photolithography, thin-film deposition).

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Assistant%2C-School-of-Computing/33375-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The National University of Singapore invites applications for the position of Research Assistant in the Department of Computer Science, School of Computing (SoC). SoC is strongly committed to research excellence in all its dimensions: Searching for fundamental results and insights, developing novel computational solutions to a wide range of applications, building largescale experimental systems, developing theories and policies for effective management of information systems in organizations, and improving the well-being of society. We seek to play an active role both internationally and locally in the core and emerging areas of Computer Science and Information Systems.

Our research will focus on the design and implementation of next-generation AI accelerators, including the development of new architecture designs (dataflow designs), reuse patterns, caching and the development of the infrastructure of the system needed to support the acceleration of AI platforms.

The Research Assistant will be responsible for working closely with the Principal Investigator and lab members on one or more research projects. He/she should possess experience or interest in at least one of the following research areas:

• Artificial Intelligence and Machine Learning
• Hardware Design, Circuits and Systems
• Algorithms
• Programming Languages & Software Engineering

Only shortlisted candidates will be notified.

Job Requirements

• A Bachelor’s degree with Honours in a relevant area; and
• Experience in research