Total 419 Science / R&D / Research job vacancies in George Town

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-in-Quantum-Algorithms-and-Machine-Learning/32457-en_GB/

We regret that only shortlisted candidates will be notified.

About the Centre for Quantum Technologies (CQT)

The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena. Experts in this new discipline of quantum technologies are applying their discoveries in computing, communications, and sensing. 

CQT is hosted by the National University of Singapore. The Centre also has staff at the Agency for Science, Technology and Research, Nanyang Technological University, Singapore, and the Singapore University of Technology and Design. With some 200 staff and students, it offers a friendly and international work environment

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

Job Description

We are seeking a promising Research Assistant to join an advanced research project at the intersection of quantum computing and machine learning, focused on developing scalable and coherent training methods for quantum models.

This project tackles one of the central challenges in quantum machine learning: how to train quantum systems efficiently and reliably on scaling quantum hardware. The research will develop novel optimization frameworks based on quantum dynamics and apply them to advanced learning architectures.

The successful candidate will contribute to both theoretical advances and experimental implementations, with opportunities to co-author publications and engage with leading researchers in the field.

Main Responsibilities:

• Develop and implement quantum learning models
• Design and evaluate novel quantum optimization and training algorithms
• Perform large-scale simulations using frameworks such as Qiskit and PennyLane
• Potentially execute experiments on state-of-the-art quantum hardware
• Benchmark quantum models against classical and hybrid baselines
• Contribute to research publications at leading venues
• Develop reusable, high-quality research code and contribute to open-source tools

Qualifications

• Master’s or PhD in Computer Science, Physics, Mathematics, or a closely related field
• Mathematical foundation, particularly in linear algebra, probability, and optimization
• Background or strong interest in quantum computing, quantum information, or quantum algorithms
• Knowledge of machine learning (e.g., deep learning, optimization, or learning theory)
• Programming skills in Python and experience with scientific computing (e.g., NumPy, SciPy, PyTorch)
• Experience with numerical simulations, algorithm design, or high-performance computing is advantageous
• Familiarity with quantum software frameworks (e.g., Qiskit, PennyLane, Cirq) is preferred
• Experience with research or advanced technical projects
• Analytical thinking, problem-solving skills, and intellectual curiosity
• Ability to work both independently and collaboratively in a research environment
• Strong scientific writing and communication skills

More Information

Interested applicants should submit the following documents to the NUS Career Portal:

• Curriculum Vitae (CV)
• Academic transcripts
• Cover letter (1-2 pages) outlining research interests and relevant experience
• Sample of technical work (e.g., paper, report, or code repository)
• Contact information for 2 referees (Letters may be requested at a later stage)

For more information, please reach out to lpira@nus.edu.sg

We encourage applications from candidates with diverse backgrounds. Applicants who do not meet all the listed criteria but are interested in the role are encouraged to apply.

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-%28Quantitative%29/32455-en_GB/?st=62AB6BB745B72DCB57CD58FD3DC1A95BEA2FBF0E

We regret that only shortlisted candidates will be notified.

Job Description

Applications are invited for the following full-time position in the Saw Swee Hock School of Public Health:

Research Assistant

We are looking for research assistants with a quantitative background for ongoing research in Public Health.

The successful candidate will be working within the team under the Principal Investigator Assistant Professor Akira Endo, collaborating closely with multiple experts.

Methods include renewal process, network transmission modelling, machine learning and Bayesian inference, particularly in the context of epidemiology and dynamics of respiratory, sexually transmitted, and tick-borne infections.

Candidates should have a solid understanding of infectious disease dynamic modelling and statistical modelling, with a sufficient background in public health, mathematics, and data science. Proficiency in R programming is essential, and we will also appreciate candidates with extensive coding knowledge of C++, Python, or Julia.

The candidate will be working with the Principal Investigator(s) on the analysis of predicting future trajectories of epidemics and assessing the potential impacts of response strategies using a range of modelling frameworks, including mathematical, statistical, and machine-learning approaches.

The Principal Investigator(s) is seeking an independent worker who is well-organised, analytical and codes competently. They will, however, be receiving support from a team of mathematicians, epidemiologists and statisticians, and have a diverse portfolio of tasks. Under the team’s guidance, they will be expected to co-lead their own publications.

We welcome academic creativity and will be highly supportive of candidates who wish to either pursue academia or desire for career progression provided they show self-motivation to showcase their problem-solving abilities.

Responsibilities:

• Infectious disease modelling
• Statistical analyses
• Stochastic processes
• Academic writing and publication of results
• Preparation of meeting materials for stakeholders

Requirements:

• Completed an MSc in a quantitative discipline (statistics, mathematics, computational biology, data science)
• Extensive experience in data science research and experience in leading at least one quantitative health-related research project
• Strong programming skills (at least one of R/Python/Julia)
• Statistical competence (understands and can perform likelihood-based inference, ideally including Bayesian)

Please email the PI at aendo@nus.edu.sg for further details.

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-AssistantAssociate-Policy-Analyst-Retirement-Adequacy/32451-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Research Assistant/Associate Policy Analyst – Retirement Adequacy

The Saw Swee Hock School of Public Health (SSHSPH) at the National University of Singapore (NUS) is recruiting a Research Assistant/Associate Policy Analyst. Rapid population ageing in Singapore raises important questions about financial resilience and retirement adequacy. This project aims to examine how life-course transitions in employment, health, caregiving, and housing shape income, expenditure, and financial vulnerability in later life. The study will draw on longitudinal datasets, including the Retirement and Health Study and will involve quantitative analysis and policy-relevant modelling to inform retirement and ageing-related policies in Singapore. This is a full-time position based in Singapore.

Duties may include, but are not limited to: (1) providing programming support for research projects; (2) conducting statistical and econometric analyses using longitudinal data; (3) managing large and complex datasets; (4) constructing indicators of retirement adequacy and financial vulnerability; (5) supporting policy modelling; (6) conducting literature reviews; and (7) contributing to scientific manuscripts, reports, and dissemination of findings.

The appointed candidate should: (1) hold at least a bachelor’s degree; (2) be proficient in Stata or R; and (3) have training in statistics, mathematics, economics, computer science, quantitative social science, public health, epidemiology, or a related field. Experience with longitudinal data analysis or microsimulation modelling is preferred. Familiarity with C++ is advantageous but not required.

The ideal candidate should demonstrate the ability to work with large datasets and have strong knowledge of quantitative methods. Strong analytical thinking and work ethics, attention to detail, and problem-solving skills are essential. Excellent written and spoken English is required, as the candidate will engage with stakeholders and contribute to reports and publications.

The position is for one year but can potentially be extended. The grade of appointment will be accorded based on candidate’s academic qualifications and years of relevant experience.

Applicants should send the following by email to the NUS Career Portal:

1) Cover note introducing themselves (no more than 500 words);
2) A two-page Curriculum Vitae (only including relevant information), containing details of two named referees;
3) A sample of published work and their roles in the projects, if applicable.

Interviews will be face-to-face for candidates. We are accepting applications until the position is filled.

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-%28Quantitative%29/24918-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Applications are invited for the following full-time position in the Saw Swee Hock School of Public Health:

Research Assistant

We are looking for research assistants with a quantitative background for ongoing research in Public Health.

They will be working within the team under the Principal Investigator Assistant Professor Borame Dickens alongside multiple collaborators and experts.

Methods include agent based/individual based modelling, SEIR modelling, geospatial statistics, Bayesian statistics, burden mapping, measuring the impact of the environment on disease among others. The PI has projects in both infectious and chronic disease, measuring the impact of interventions.

Candidates need to be able to understand statistical modelling, have a mathematical background, and be fluent in R programming. We will also consider candidates who have extensive C++ or Python coding knowledge as these are transferrable to R.

The candidate will be working with the Principal Investigator(s) on the analysis of national health datasets, utilising an array of methods to infer statistical relationships and health outcomes. Further mathematical modelling will also be carried out when necessary involving diagnostic flows and where appropriate, disease spread and/or illness progression.

The Principal Investigator(s) is seeking for an independent worker who is well-organized, analytical and codes competently. They will however be receiving support from a team of mathematicians, epidemiologists and statisticians, and have a diverse portfolio of tasks. Under the team’s guidance, they will be expected to co-lead their own publications.

We welcome academic creativity and will be highly supportive of candidates who wish to either pursue academia or desire for career progression provided they show self-motivation to showcase their problem-solving abilities.

Responsibilities:

• Disease modelling
• Statistical analyses
• Academic writing and publication of results
• Preparation of meeting materials for stakeholders

Requirements:

• Completed a BSc in a quantitative discipline (statistics, mathematics, computational biology, data science).
• Strong programming skills (R preferred)
• Statistical competence (Bayesian is advantageous)

Please email the PI at ephdbsl@nus.edu.sg for further details/

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-%28Computer-Science%29/32470-en_GB/?st=268F709592288E636706A7A9A3F4FD9E1228D918

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 large-scale experimental systems 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.

The successful candidates will be responsible for working closely with the Principal Investigator and lab members on one or more research projects. 

Only shortlisted candidates will be notified.

Job Requirements

•  Bachelor’s or Master's degree in Computer Science
•  Experience in Research
•  Demonstrated ability to carry out independent research or project work.
•  Excellent communication, documentation, and teamwork skills.

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-AIML-Failure-Analysis/32444-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The ECE Department at NUS is seeking a Research Fellow to support applied AI research in failure analysis and fault isolation. The successful candidate will focus on developing and integrating machine learning–guided failure analysis and diagnostic capabilities for hybrid electronics. This position offers an exciting opportunity to work at the forefront of semiconductor technology, with close collaboration across industry partners and academic researchers.

Responsibilities will involve:
1.    Research & Development
•    Conduct research on AI/ML techniques for semiconductor failure analysis.
•    Develop novel algorithms and methodologies for defect detection, classification, and failure analysis.
•    Supervise and mentor junior researchers and graduate students in related research activities.
2.    System Integration
•    Lead the design and integration of ML-driven diagnostic tools into failure analysis workflows.
•    Build robust and scalable software solutions interfacing with diagnostic instruments and test platforms.
•    Drive optimization of system performance for real-world deployment.
3.    Data Analysis & Reporting
•    Manage the collection, preprocessing, and large-scale analysis of experimental and simulation datasets.
•    Validate and benchmark AI-driven predictions against empirical outcomes.
•    Prepare technical reports, publications, and presentations for both academic and industry audiences.
4.    Project Management & Collaboration
•    Take responsibility for delivering research milestones within project timelines.
•    Serve as the primary liaison with industry partners to align objectives and ensure impactful outcomes.
5.    Innovation & Intellectual Property
•    Drive innovation in diagnostic methodologies and failure analysis workflows.
•    Contribute to patent filings, technology disclosures, and commercialization efforts.
•    Publish findings in high-impact journals and present at leading conferences.

Qualifications

•    Ph.D. or equivalent degree in Electrical, Electronics, Mechanical, Chemical Engineering, Physics, Material Science or its equivalent from a reputable University/Institute is preferred, or equivalent related experience. 
•    Candidate with experience in microelectronic research, characterisation, metrology and electrical testing, and strong in data analysis will have advantage.
•    Proficiency in data analysis and interpretation using statistical tools and software packages.
•    Excellent communication skills and the ability to work effectively in a collaborative research environment.
•    Motivated and possesses effective communication skills including writing and presenting.
•    Ability to work independently and collaborate within a diverse team.
•    Open to Fixed Term Contract.

Position Overview:

Black Sesame Technologies is a rapidly expanding artificial intelligence company backed by substantial VC funding, dedicated to pioneering algorithms and chips for artificial intelligence and image processing. As a Research Scientist in this role, you will collaborate closely with leading researchers to forge cutting-edge perception algorithms aimed at tackling real-world challenges in autonomous driving and beyond. The primary focus of perception is to identify and comprehend the surrounding environment of autonomous vehicles, supporting L2 and L3 automated driving capabilities. This involves constructing a real-time virtual representation of the local environment by processing input data predominantly from cameras, alongside data from complementary sensors such as radars, IMU, and ultrasonic sensors.

Job Description:

• Develop deep learning-based perception algorithms encompassing object detection, lane detection, segmentation, depth estimation, and other related tasks.
• Innovate state-of-the-art network architectures and training methodologies, assessing their efficacy in addressing vision-related challenges.
• Execute deep network compression tailored for ASIC platforms.
• Stay abreast of the latest advancements in deep learning and computer vision literature, proactively proposing novel concepts.
• Contribute to patent and research paper publications.

Job Requirements:

- Master Degree/ PhD in Computer Science, electrical engineering, or a related field.

- Possess 3+ years of experience in computer vision / machine learning development.

- Demonstrated expertise in research and development within one or more of the following domains:

• Deep network development, particularly with visual data.
• Object detection and tracking.
• Stereo / optical flow / depth estimation.
• Multi-view geometry and 3D computer vision.
• Structure from motion.
• Network compression and optimization.
• Network-based sensor fusion.
• Mathematical optimization.
• Proficient programming skills in Python (knowledge of C++ is advantageous).

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-AssistantAssociate-Policy-Analyst-Economic-Evaluation/32452-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Research Assistant/Associate Policy Analyst – Economic Evaluation

The Saw Swee Hock School of Public Health (SSHSPH) at the National University of Singapore (NUS) is recruiting a Research Assistant/Associate Policy Analyst. Rapid population ageing in Singapore underscores the need for effective interventions to support healthy and active ageing. This project aims to evaluate the impact of interventions (e.g. Age Well SG and related community-based programmes) on health outcomes, functional status, healthcare utilisation, and wellbeing among older adults. The study will draw on longitudinal and administrative datasets and will involve quantitative analysis and policy-relevant modelling to inform ageing and healthcare policies in Singapore. This is a full-time position based in Singapore.

Duties may include, but are not limited to: (1) providing programming support for research projects; (2) conducting statistical and econometric analyses using longitudinal and administrative data; (3) managing large and complex datasets; (4) evaluating programme impacts on health, frailty, and healthcare utilisation; (5) supporting cost and policy modelling; (6) conducting literature reviews; and (7) contributing to scientific manuscripts, reports, and dissemination of findings.

The appointed candidate should: (1) hold at least a bachelor’s degree; (2) be proficient in Stata or R; and (3) have training in statistics, mathematics, economics, computer science, quantitative social science, public health, epidemiology, or a related field. Experience with programme evaluation, longitudinal data analysis, or microsimulation modelling is preferred. Familiarity with C++ is advantageous but not required.

The ideal candidate should demonstrate the ability to work with large datasets and have strong knowledge of quantitative methods. Strong analytical thinking and work ethic, attention to detail, and problem-solving skills are essential. Excellent written and spoken English is required, as the candidate will engage with stakeholders and contribute to reports and publications.

The position is for one year but can potentially be extended. The grade of appointment will be accorded based on the candidate’s academic qualifications and years of relevant experience.

Applicants should send the following to the NUS Career Portal:
1) Cover note introducing themselves (no more than 500 words);
2) A two-page Curriculum Vitae (only including relevant information), containing details of two named referees;
3) A sample of published work and their roles in the projects, if applicable.

Interviews will be face-to-face for candidates. We are accepting applications until the position is filled.

Job profile:

Research Assistant - HumanSciences Methodology for Agent-Based Modelling

DesCartes Programme WP1× WP6

Context

The DesCartes Programme, led by CNRS@CREATE in Singapore, brings together AI, engineering and human sciences to design trustworthy hybrid AI systems. In partnership with the National University Health System (NUHS), WP1 (Agent-Based Modelling) and WP6 (Ethics of Autonomy and Care in AI Decision-Making) are jointly developing an agent-based model (ABM) to support the redesign of selected NUH services. Grounding this model in empirically rich descriptions of care practices, patient trajectories and staff routines requires dedicated field-based human sciences work.

Mission

Working at the interface between WP1 and WP6, the Research Assistant will contribute to the design and implementation of human sciences methodology feeding into the ABM.Main tasks:

- Design and conduct field observations.

- Prepare and carry out semi-structured interviews with healthcare staff, patients and caregivers; transcribe and analyse the material (thematic/qualitative analysis).

- Translate qualitative findings into structured inputs for the ABM in close collaboration with the WP1 modelling team.

- Participate in joint WP1-WP6 meetings, internal reports, and co-author scientific outputs.

Profile

- Master's degree (or equivalent) in psychology, sociology, anthropology, public health, human factors, cognitive science or related field.

- Solid training in qualitative methods.

- Interest in interdisciplinary work with computer scientists/modellers; basic familiarity with ABM or simulation approaches is a strong asset.

- Experience in clinical / hospital environments is a plus.

- Excellent working English; additional languages spoken in Singapore (Mandarin, Malay, Tamil) are appreciated.

- Autonomy, rigour, strong interpersonal and writing skills.

Practical Information

- Location: Singapore, CREATE Tower,

- Contract type & duration: 6 months, possibility of extension

- Start date: mid-July

- Salary: range, SGD5,500 - SGD7,200

- Supervision: Prof. Bahia Guellai (WP6) and Blaise Genest (WP1)

Application

Please send a CV, a short cover letter and the contact details of two referees to bahia.guellai@cnrsatcreate.sg, with the subject line RA - WP1×WP6. Applications will be reviewed on a rolling basis until the job is filled.

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%2C-Computer-Science-%28School-of-Computing%29/32440-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The appointee will independently spearhead a high-impact research agenda in human-AI co-creativity, which intersects HCI, Generative AI, and Educational Theory. Centering on the lab’s mission to scaffold rather than substitute human expertise, the candidate will conceptualize and lead projects that investigate how AI can be architected as interactive tutors or palettes to empower creativity.

Responsibilities extend beyond project execution to include: shaping the lab’s strategic research direction regarding the ethical and cognitive implications of AI in creative workflows; forging and managing high-level collaborations with external academic and industrial partners; and leading the design of novel evaluative frameworks to measure the long-term development of a user's artistic vision. The appointee will also play a critical role in lab mentorship, acting as a senior advisor to PhD students, and will take a proactive lead in securing research funding through grant proposal development.

Qualifications

The successful candidate must possess a PhD in Human-Computer Interaction, Computer Science, or a related field, with a distinguished track record of independent research as evidenced by first-author publications in flagship venues (e.g., CHI, UIST). Candidates must demonstrate a strong ability to synthesize AI capabilities with complex human needs, specifically in the domain of creativity and expertise development. We are particularly seeking scholars who can leverage Singapore’s unique multicultural landscape to pioneer situated, context-aware AI systems that honor and amplify local creative practices.

Beyond technical excellence in building AI-powered systems, the role requires exceptional intellectual leadership and the capacity to critique and evolve the lab’s core philosophies. The candidate will lead efforts to center underrepresented perspectives within the Singaporean and broader Southeast Asian sociotechnical context to challenge and expand global AI design paradigms. Proven experience in mentoring junior researchers and a demonstrated potential for successful grant writing are highly desirable. The candidate should be prepared to operate as a senior member of the laboratory, contributing significantly to its intellectual atmosphere, lab culture, and professional standing.

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Engineer-%28AI-Driven-Autonomous-&-Smart-Manufacturing%29%2C-Division-of-Industrial-Design/32423-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

NUS Centre for Additive Manufacturing (AM.NUS) is inviting applications for the position of Research Engineer in AI-Driven Autonomous and Smart Manufacturing, with a focus on Additive Manufacturing (AM). 

•    Develop AI-driven frameworks that integrate LLMs, agentic AI, and multimodal foundation models for autonomous and smart manufacturing applications, with emphasis on additive manufacturing.
•    Fuse multimodal sensor data, reinforcement learning, and vision–language models to enable real-time defect detection, process monitoring, and intelligent decision-making.
•    Support internal capability development and execute collaborative projects with academic researchers and industry partners.
•    Assist in preparing technical reports, documentation, and contribute to publications and grant proposals where applicable.
•    Assist laboratory safety and procurement whenever necessary.

AM.NUS leverages the National University of Singapore world-class faculties, expertise and advanced capabilities in 3D printing technology, to bring innovative products to the field of healthcare that will improve patient outcomes and change lives for the better. 
AM.NUS explores a whole new dimension in medicine, applying ground-breaking 3D printing technology for personalised patient treatments.

AM.NUS is the only multi-disciplinary Additive Manufacturing (AM) centre in an Institute of Higher Learning in Singapore which comprises five Faculties (Medicine, Science, Engineering, Dentistry and Design & Environment). The Centre is supported both internally by NUS and externally by National Additive Manufacturing Cluster (NAMIC) and Singapore Economic Development Board.

Qualifications

●    Bachelor degree in Mechanical Engineering, Manufacturing Engineering, Computer Science, Artificial Intelligence, Industrial Design or a closely related field.
●    Strong background in additive manufacturing and smart manufacturing systems.
●    Proven expertise in machine learning and AI, including experience with LLMs, multimodal models, or reinforcement learning.
●    Experience with engineering design and simulation tools (e.g., AutoCAD, SolidWorks, FEA) is an advantage.
●    Experience with digital twins, knowledge graphs, or cyber–physical systems is an advantage.
●    Proficiency in written and spoken English. 

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Engineer-%28AI-Accelerator-and-Energy-Efficient-Computing%29/32425-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are seeking a highly motivated and skilled Research Engineer to join our team in developing next-generation energy-efficient AI hardware. The project aims to demonstrate an AI accelerator chiplet that integrates emerging non-volatile memory (RRAM or MRAM) with conventional I/O interfaces. This platform will showcase compute–memory co-design advantages, including enhanced data throughput, improved energy efficiency, and reduced data-movement overheads for large-scale AI workloads. 

Key Responsibilities:
•    Develop and implement fine-grained dynamic voltage and frequency scaling (DVFS) strategies tailored for GPU-based AI workloads, with control at the level of transformer blocks and attention layers.
•    Design and build a high-resolution (microsecond-scale) performance monitoring framework to capture workload intensity, memory access patterns, and GPU utilization for real-time optimization.
•    Develop and deploy machine learning models to predict optimal voltage–frequency operating points during LLM training and inference.
•    Integrate predictive control algorithms with hardware platforms to enable real-time, adaptive power management across heterogeneous compute and memory subsystems.
•    Collaborate on system-level hardware–software co-design to realize energy-efficient AI acceleration.
•    Contribute to prototype development, benchmarking, and evaluation of performance and energy efficiency.
•    Publish research findings in leading journals and present at international conferences.
•    Mentor undergraduate students and support team-based research activities.

Qualifications

•    Bachelor’s or Master’s degree in Computer Engineering, Computer Science, or a related field.
•    Strong programming skills in Python and C/C++, with experience in machine learning frameworks such as PyTorch or TensorFlow.
•    Familiarity with deep learning models—particularly transformer architectures and large language models (LLMs)—is advantageous.
•    Experience or interest in system-level optimization (e.g., DVFS, workload profiling, or power management) is a plus.
•    Strong analytical and problem-solving skills, with the ability to conduct independent research and contribute to technical publications.
•    Ability to work effectively in a multidisciplinary environment, with good communication skills, initiative, and adaptability.

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-%28LKYSPP%29-%2832429%29/32429-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are seeking a full-time Research Assistant (Quantitative Analysis) to work on empirical research in the area of population aging, mortality, and pensions, with an active focus on Singapore and Asia. The project is part of a larger interdisciplinary research program aimed at developing a better understanding of how aging beliefs and mortality expectations may influence financial decision-making among participants in a pension scheme. The Principal Investigator of this project is Associate Professor Joelle Fong. 

The LKY School of Public Policy is part of the National University of Singapore, which is Asia’s top university in the QS World University Rankings.

Candidates should have a background in Statistics, Economics, or Risk Management & Insurance.  Knowledge of mortality analysis and life table methods is required. Candidates with also some knowledge and experience in how pension systems function will be a good fit. The successful candidate must demonstrate good overall competence in quantitative research methods and be proficient with statistical software such as STATA or R.  Due to the nature of the role, excellent written and spoken English is essential. 

Other responsibilities include:

• Assist with drafting literature review and questionnaire design
• Assist with data analysis in R and STATA (data collection / cleaning)
• Research administration support 
• Other ad-hoc duties as assigned

The full-time position will have a 12-month term.

Qualifications

• Master’s degree or equivalent in Statistics, Economics, or Risk Management & Insurance, from a reputable university
• Familiar in working with large datasets for statistical analysis
• Demonstrate good organisational and analytical skills
• Responsible and detail oriented
• Must be able to self-motivated, able to work independently, as well as in a team

The candidate is expected to be physically present in office during the stipulated working hours, and able to commit to at least 1 year of service. 

Benefits:

• Internationally competitive salary, 1-year contract
• Salary and appointment will be commensurate with the candidate’s qualifications, track record, potential, experience
• Highly collegial working environment with an internationally diverse group of scholars
• Excellent research support provided by the School and NUS

Application Procedure:

Interested applicants are invited to send the following list of documents via the NUS Career Portal.

• Cover letter
• Curriculum vitae
• Three writing samples

Your cover letter should include details such as your highest qualifications, past research experience, last drawn salary (if applicable), expected salary, and country of citizenship. Please also state when you can begin work, if you are selected for the role.

Applications will be accepted until the position is filled. Should you be shortlisted, a faculty member or an administrator will contact you directly for an interview. 

Job Description

The Ho lab is a world leader in the study of small open reading frame–encoded peptides (SEPs), with particular expertise in identifying novel peptides essential for mitochondrial function and metabolism. We previously discovered new mito-SEPs (mitochondrial sORF-encoded peptides) (Zhang et al., 2020, Nature Communications) and are working on defining their molecular functions, with a special focus on the those involved in immune-metabolism. Through this work, we aim to uncover new concepts in the metabolic regulation of immune function. The lab uses a combination of bioinformatics, biochemistry, animal modelling, CRISPR screening and single-cell omics in human and mouse systems to understand how mito-SEPs regulate cellular processes related to energy production. For more information, please visit www.ho-lab.org.

We are seeking a collaborative, dynamic and self-motivated Senior Research Fellow to join the team. The selected candidate will perform a variety of research activities, including but not limited to the following:

• Conduct research to address how oxidative phosphorylation and its associated metabolites control innate and adaptive immunity against pathogen infection.
• Write and review research papers, present research outcomes, conceptualise new ideas and develop plans for independent research which could have a considerable influence and impact on the relevant field attracting research funding.
• Provide support for external grant/protocol development, study design and management of research activities.
• Maintain optimal experiment progress in the laboratory or in the research work undertaken.
• Perform other related duties incidental to the work described therein.

Job Requirements

• PhD in a related scientific area and/or post-graduate medical degree with at least 3 years of relevant research experience.
• Possesses expertise and interest in the following areas: Mitochondrial biology, innate and adaptive immunology, immuno-metabolism, inflammation or host-pathogen immune interactions, bioinformatics surrounding metabolic modelling, single-cell or spatial transcriptomics, and mouse models of infection and inflammation.
• Knowledge of the scientific background relevant to the research area and laboratory experimental skills.
• Proven track record in the form of high impact publications.
• Demonstrated capability of research independence progressively.
• Strong writing and critical thinking skills, as well as good communication and presentation skills.
• A team player who is able to prioritise, multi-task and work collaboratively in a diverse workforce.

We regret that only shortlisted candidates will be notified.

Research Associate in Implementation and testing of AI models – Embodied AI

The project Embodied AI for Human-Robot Collaborative Task Execution is looking for a Research Associate in Embodied Artificial Intelligence (EAI) – Enhancing robotic foundation models for human-robot collaborative task execution. The overall goal of this project is to investigate how robotic platforms can combine the capabilities of robotic foundation models (VLAs/VLMs)in generalized reasoning and policy formulation with RL-based approaches for trajectory and manipulation generation to provide fast, optimized and anticipatory assistance to humans while co-executing a task.

DESCRIPTION OF THE JOB POSITION

You will be part of our team developing fundamental capabilities that combine recent and rapid  advances in robotic foundation models with traditional control-based approaches for human-robot collaborative task execution for various industrial tasks.

The successful candidate will be involved in some or all of the following tasks:

•             Software development activities, involving implementation of AI algorithms (e.g., Training models for computer vision, robotics, multi-modal perception etc.), along with maintenance of relevant in-house hardware and software systems for experimental EAI testbeds.

•             System integration of robotic modules for real-world demonstrations of robotics applications. Efficient implementation of AI models on resource-constrained devices (Eg. Jetson family of devices, robotic platforms, VR/XR platforms such as HoloLens).

•             Development of experimentation and data collection platforms for EAI research involving human-robot collaboration, including activities such as effectively setting up sensors on the robots as well as wearable sensors on human subjects performing joint-tasks with the robots.  

•             Actively participate in R&D activities including data collection experiments, software development, testing and deployment of intelligent systems and scientific writing/demonstrations.

EXPERIENCE & QUALIFICATIONS

Minimum:

– Bachelor or Masters Degree in a relevant field of Engineering (Computer Science, Electrical, Electronics, Robotics etc.).

– Background and experience in the following areas: Implementation and testing of AI models; Development activities for edge AI on resource-constrained devices; Experience with wearable platforms such as HoloLens, EMG/IMU units.

– Experience with camera-based and non-camera based sensors(mmWave RADARS, LiDARs etc) for sensing and monitoring of human movements and activities; Experience in robotic software development (ROS, Gazebo, Isaac Sim).

– Experience with hardware platforms such as Jetson, ESP32, Commercially available robots and drones etc.; Experience in system administration and maintenance of computer servers and systems involving multiple high-end GPUs.

– Hands-on experience in using latest machine learning frameworks for model development and experimentation.

FURTHER INFORMATION & CONTACT

Gross Monthly Salary Range (SGD): 5,500 to 7,000 (depending onsuitability and experience).

Duration of the contract: 1 year contract

Workplace address: CREATE Campus, CREATE Tower, 1 Create Way #08-01 Singapore 138602.

Interested applicants, please send your your full CV, with the names and contacts(including email addresses) of two-character referees to:

–      Archan MISRA archanm@smu.edu.sg

–      Vigneshwaran Subbaraju vigneshwaran_subbaraju@a-star.edu.sg