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

At NUS Singapore, our people are the driving force behind our success. We pride ourselves on fostering a vibrant and inclusive community of talented individuals from diverse backgrounds.

When you join NUS, you become part of a community of passionate individuals who are dedicated to driving innovation and change in education, research, and service. Our culture of inclusivity and entrepreneurship means that you’ll have the freedom to explore your ideas and make a meaningful impact. Your career at NUS is more than just a job - it’s a transformative experience that will shape your personal and professional growth.

Explore the link provided to learn additional details about the available job opportunity:
https://careers.nus.edu.sg/job/Visiting-Research-Associate-Professor-%28Institute-for-Functional-Intelligent-Materials%29/32674-en_GB/?st=78E0AE07129EE61FBEAFCAE8FC083458771292BE

Job Details

Location: Kent Ridge

Working Hours: Mon-Fri, Office Hour

Work Type: 3-Month Contract

Salary: Up to $ 4,000 per month

Our client is seeking a dedicated Temporary Research Officer to support multidisciplinary projects in the area of child health and early-life development. The research focuses on the epidemiology of diseases in children and the impact of the exposome during the early developmental phases of life on early life outcomes. Majority of the work is based in the birth cohorts Growing Up in Singapore Towards healthy Outcomes and Singapore Preconception Study of Long-Term Maternal and Child Outcomes. The selected candidate will be involved in microbiome and statistical data analysis.

What you will be working on?

The ideal candidate will be involved in microbiome research, statistical analysis, and contributing to the production of scientific outputs.

• Perform statistical data analysis, including microbiome datasets
• Conduct literature reviews to support ongoing research
• Assist in the development of scientific papers and dissemination of research findings
• Provide administrative and operational support for research activities

What are we looking for?

• Singaporean only
• Bachelor’s Degree in Biomedical Science or relevant discipline
• Knowledge of microbiome and statistical analysis (e.g. R and SPSS) is advantageous
• Prior research experience is advantageous
• Highly motivated and able to work independently

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Carmen Tan Huei Mun | R23115837

ScienTec Consulting Pte Ltd (ScienTec Personnel) |11C5781

We are looking for a passionate tester to join our team. In this role, you will work on projects involving the digital onboarding of insurance products and services. This includes working across various digital touchpoints and supporting the implementation of changes to our business systems. You will be required to understand the end-to-end integration between internal stakeholders, as well as the business requirements. You will work closely with Business Analysts and users from various departments to ensure all test scenarios are thoroughly covered, enabling the smooth implementation of system changes.

PRIMARY RESPONSIBILITIES

• Work closely with BA/Users to understand business requirements
• Create test scenarios and test cases
• Create test data
• Ensure test cases are manually executed in accordance with priority assigned
• Conduct functional and end-to-end testing
• Document all test results for verification
• Log testing defects for errors encountered during test execution
• Provide clarifications to the developer on the logged error
• Track and report testing progress and defects resolution progress
• Re-test fixed defects to ensure proper closure
• Initial investigation and verification of error against the business requirements
• Support test manager to track and report testing progress and defects resolution progress
• Re-test fixed defects to ensure proper closure
• Create and execute of automated tests
• Support User Acceptance Test Planning & automated and manual testing

Looking for:
• Minimum one year experience as tester, preferably testing insurance related application.
• Able to work under pressure and within tight deadlines
• Familiar with Microsoft 365 - Office tools (Word, Excel, PowerPoint), Teams, SharePoint.
• Good Technical writing capability and communication skills
• Good communication, problem solving and analytical skills.
• Hardworking, dynamic, strong responsibility and a good team player
• Experience with Automated testing would be an advantage

The Academic Instructor is required to teach the courses in the undergraduate programs offered by the University at Buffalo, The States University of New York, US, in partnership with Singapore Institute of Management in Singapore.

The roles would include:
• Creation of course design and materials, and implementation of syllabus to meet UB learning objectives;

• Delivery of student-centered, interactive course curriculum, including supervision of project work;

• Create, administer, and mark assessment instruments;

• Evaluate student progress and achievements;

• Hold regular consultation hours;

• Maintain and submit academic records.

Job Requirements:

• A Ph.D or Master's Degree in the exact discipline as specified by the teaching assignment from a nationally or regionally (USA) accredited university is required;

• Terminal degree is preferred;

• At least 2 years of relevant full-time teaching experience in the exact discipline as specified by the teaching assignment at the tertiary level is required;

• Ability to independently operate all class level functions of Blackboard classroom management system, including Grade Center is required;

• Substantial evidence of an active academic research agenda and recent history of publication(s) in peer-reviewed scholarly journal(s) are strongly preferred;

• Available to teach during daytime on weekdays.

PositionOverview

This rolewill be responsible for the operation and management of the AI academiccommunity, GAIR DAO Community (www.gairdao.com),while also driving engagement and collaboration with academic resources andresearchers.

KeyResponsibilities

1.Academic Outreach & Partnership Development

• Leverage local Singapore universities (such as NUS, NTU, and SMU) to proactively maintain and expand long-term relationships with AI researchers, PhD students, and leading research laboratories, building a stable academic collaboration network.
• Establish and maintain connections with a broader academic audience, including authors of high-impact research papers and overseas Chinese students, through participation in international academic conferences and other technology-related events.
• Convert established academic connections into long-term collaborations, such as inviting scholars to participate as guests on our podcast series “GAIR Live” , or engaging them in academic content co-creation initiatives.

2.Community Content Operations & Management

• Publish and synchronize key content produced by other team members (e.g., conference summaries, paper reviews, and research insights) to the GAIR DAO community platform, while facilitating meaningful discussions.
• Increase community engagement and user participation through effective community management strategies.
• Proactively propose and implement improvements to content production, engagement activities, and operational workflows.
• Regularly generate operational reports, analyze key performance indicators such as community growth and engagement rates, and provide actionable recommendations.

Qualificationsand requirements

• Excellent verbal and written communication skills in both English and Chinese.
• Results-oriented, highly organized, and capable of managing multiple tasks while maintaining consistent content output and achieving objectives.
• Strong interest in or understanding of artificial intelligence and international academic conferences.
• Prior experience in academic outreach, research community management, or related fields is preferred, such as participation in academic conferences or collaborations with universities and research institutions.
• Singapore or PR only .

WorkEnvironment & Travel Requirements

This rolerequires participation in leading international academic conferences heldworldwide. Key responsibilities at these events include:

• Networking with scholars and maintaining records of relevant contacts and information.
• Supporting conference-related content development and gathering materials for future content creation.
• Contributing to timely original content such as conference highlights, quick commentary, and event recap articles.

Interestedparties, please sent detail resume to : admin@gair.sg

We arecommitted to building a global academic content platform and look forward towelcoming you to our team.

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-%28Digital-Twin-of-Data-Center%29/33224-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

This project aims to develop intelligent control and digital-twin methods for energy-efficient data center thermal management. The work will involve modeling and simulation of data center cooling systems, together with the development of advanced control strategies. The candidate will use operational data, computational modeling, and optimization techniques to improve cooling energy efficiency, thermal reliability, and control robustness under dynamic IT workloads and environmental conditions.

Qualifications

•             PhD degree in mechanical engineering, control engineering, energy systems, or a related field.

•             Strong background in thermal-fluid systems, data center cooling, digital twins, and intelligent control.

•             Experience in Python/MATLAB, numerical simulation, and data-driven modeling.

•             Experience in model predictive control or reinforcement learning is preferred.

•             Good publication record in energy-efficient cooling or AI-assisted energy systems is desirable.

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-%28Interdisciplinary%29%2C-ChBE/33228-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Positions are available for Research Fellows (or Post-doctoral Fellows) in the research group of Prof. Siowling Soh, at the Department of Chemical and Biomolecular Engineering, National University of Singapore (NUS).  

The group’s general program of research involves the coupling of organic materials, mechanical forces, and electrostatics at different interfaces (e.g., solid, liquid, or gas). This coupling is currently greatly under-explored and poorly understood in science. At the same time, the coupling gives rise to many fascinating new natural phenomena for exciting fundamental discoveries and development of impactful and original technologies. 

The general approach of the group is to conduct original programs and new directions of research with strong fundamental science. The group is highly interdisciplinary and involves engineering (e.g., fluid mechanics), materials science, chemistry, and physics. Different organic materials are used, including polymers (e.g., stimuli-responsive polymers), hydrogels, and covalent organic frameworks (COFs). 

One project involves an original system that harvests water energy from nature (e.g., rain and rivers) and directly generates electricity by solid-liquid charge separation with high energy conversion efficiency. Other projects involve clearing virus-laden atmospheric aerosols and preventing the spread of infectious diseases (e.g., COVID-19) and development of clean surfaces that do not adhere any dust on them. Another research involves stimuli-responsive polymers for small molecular separation, smart delivery, and intelligent soft machines.

A recent exciting and emerging field from our group is the development of novel mechanocatalysts for performing mechanochemical reactions with high energy conversion efficiency. Harvesting energy from mechanical forces of nature (e.g., wind or water flows) is a novel and sustainable approach to performing chemical reactions. 

Qualifications

The ideal candidate is preferably someone open-minded to conducting original fields of research, independent, and hardworking. Because the research of the group is highly interdisciplinary and many projects in different disciplines are ongoing, candidates with a Ph.D. from a wide range of backgrounds will be considered for different projects, including engineering (e.g., chemical, mechanical, etc), materials science, chemistry, and physics.  

For more information on the background of the research, please refer to: https://blog.nus.edu.sg/chessl/

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-%28Interdisciplinary%29%2C-ChBE/33230-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Positions are available for Research Fellows (or Post-doctoral Fellows) in the research group of Prof. Siowling Soh, at the Department of Chemical and Biomolecular Engineering, National University of Singapore (NUS).  

The group’s general program of research involves the coupling of organic materials, mechanical forces, and electrostatics at different interfaces (e.g., solid, liquid, or gas). This coupling is currently greatly under-explored and poorly understood in science. At the same time, the coupling gives rise to many fascinating new natural phenomena for exciting fundamental discoveries and development of impactful and original technologies. 

The general approach of the group is to conduct original programs and new directions of research with strong fundamental science. The group is highly interdisciplinary and involves engineering (e.g., fluid mechanics), materials science, chemistry, and physics. Different organic materials are used, including polymers (e.g., stimuli-responsive polymers), hydrogels, and covalent organic frameworks (COFs). 

One project involves an original system that harvests water energy from nature (e.g., rain and rivers) and directly generates electricity by solid-liquid charge separation with high energy conversion efficiency. Other projects involve clearing virus-laden atmospheric aerosols and preventing the spread of infectious diseases (e.g., COVID-19) and development of clean surfaces that do not adhere any dust on them. Another research involves stimuli-responsive polymers for small molecular separation, smart delivery, and intelligent soft machines.

A recent exciting and emerging field from our group is the development of novel mechanocatalysts for performing mechanochemical reactions with high energy conversion efficiency. Harvesting energy from mechanical forces of nature (e.g., wind or water flows) is a novel and sustainable approach to performing chemical reactions. 

Qualifications

The ideal candidate is preferably someone open-minded to conducting original fields of research, independent, and hardworking. Because the research of the group is highly interdisciplinary and many projects in different disciplines are ongoing, candidates with a Ph.D. from a wide range of backgrounds will be considered for different projects, including engineering (e.g., chemical, mechanical, etc), materials science, chemistry, and physics.  

For more information on the background of the research, please refer to: https://blog.nus.edu.sg/chessl/

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-%28Mathematics%29/33226-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The successful candidate will work with Asst.  Prof. Julian Sester on developing mathematical methods for Distributionally Robust Reinforcement Learning.

The main responsibilities of the position include:
•    Developing rigorous mathematical foundations for distributionally robust reinforcement learning under model uncertainty; 
•    Studying robust Markov decision processes, dynamic programming principles, and convergence properties of robust learning algorithms; 
•    Designing and analysing reinforcement learning algorithms based on Wasserstein, Sinkhorn, or related ambiguity sets; 
•    Establishing theoretical guarantees such as stability, convergence, approximation error bounds, or sensitivity estimates; 
•    Implementing and testing proposed methods in numerical case studies, with possible applications in quantitative finance, stochastic control, or risk management; 
•    Preparing research manuscripts for publication in leading journals and presenting results at seminars, workshops, and conferences; 
•    Contributing to the research environment of the group, including discussions with PhD students, postdoctoral researchers, and collaborators.

Qualifications / Discipline:

•    PhD in Mathematics, Applied Mathematics, Statistics, Operations Research, Quantitative Finance, or a closely related discipline.

Skills:
•    Strong background in probability theory, stochastic processes, stochastic control, optimization, or reinforcement learning; 
•    Solid mathematical training and ability to work with rigorous proofs; 
•    Familiarity with Markov decision processes, dynamic programming, distributionally robust optimization, optimal transport, or reinforcement learning is highly desirable; 
•    Programming skills in Python are desirable, especially experience with numerical experiments, machine learning libraries, or reinforcement learning environments; 
•    Good written and oral communication skills; 
•    Ability to work independently and collaboratively in an interdisciplinary research environment. 

Experience:
•    Prior research experience in one or more of the following areas is desirable: reinforcement learning, robust control, stochastic control, distributionally robust optimization, optimal transport, mathematical finance, or machine learning; 
•    A track record of high-quality research, demonstrated through publications, preprints, or a strong PhD thesis; 
•    Experience with numerical implementation of mathematical or machine learning methods would be an advantage; 
•    Experience in quantitative finance or financial applications is welcome but not required.

Key Responsibilities:

1. Preparation of project documentation (VO/Omission including justification, progress claim and etc)
2. Assist project personnel in issuance of PO including getting comparison quote and discussion required
3. Certification of contractor’s payment claim
4. Conduct site walk to verified work done on site
5. All contract related matters
6. Closure of Project Final Account

Requirements:

• Min Diploma in Quantity Surveying
• Minimum 2 years of relevant experience in interior renovations/construction fields is an advantage
• Strong interpersonal skills
• Proactive, responsible, and able to take initiative
• Able to start work immediately
• Singaporeans / PRs only

Job Description

• Responsible for MEP Design, taking off BOQ, sourcing the quotation and prepare quotation.
• Lead the development and submission of high-quality M&E tenders, ensuring compliance with all client requirements and deadlines.
• Attend site visit for tender briefing.
• Interpretation of tender specifications, client requirement, drawings and any other relevant documents; not limited to Project Presentation, Schedule of Rates, Technical Data, Risk Assessment, Bill of Quantity and documents needed for Tender Submissions.
• Understand how to do MEP design to comply with Singapore Standard
• Liaise with suppliers and contractors to get proposals/quotations and carry out evaluation
• Conversant with Singapore building codes and regulations
• Provide guidance and support to project teams in the implementation of successful M&E practices.
• Ensure adherence to company policies and procedures throughout the tender process.

Job Requirements:

• Minin Diploma or Degree in Electrical Engineering
• At least 3 years of relevant working experience in Interior Fitting Out M&E Works
• Preferably have knowledge on how to prepare M&E technical design, technical write-up, prepare tender specifications and presentation slide for tender interviews
• Strong in Tender Presentation Skill
• Highly self-motivated, good working attitude with high level of professionalism & integrity
• Excellent written and verbal communication skills.
• This position is only open to Singapore citizens and Permanent Residents.

Project Overview

The "Mens, Manus and Machina—How AI Empowers People, Institutions and Cities in Singapore (M3S)" five-year project was initiated in July 2023. It is driven by the goal of investigating the nature of work, redefining our relationship with technology, and exploring how institutions can adapt to foster liveability, sustainability, innovation, and social welfare.

Successful applicants will have the opportunity to work on cutting-edge projects that aim to develop state-of-the-art AI to create future smart cities. This Postdoctoral Associate position is until June 2028 under the M3S program at SMART. The SMART team seeks to advance the frontier of AI research, apply it to society and cities, and demonstrate the concrete social impacts of the AI algorithms with broad public acceptance in Singapore.

Responsibilities

The SMART-T7 project concerns the design of human-machine systems for the scheduling and allocation of valuable resources in ways that accommodate and optimize for the needs and capabilities of both humans and machines. The project aims to solve diverse use cases in a broad set of application contexts.

The management of large-scale service and infrastructure systems—such as airport operations, urban mobility, last-mile logistics, robotic fleet management and other smart city applications—requires making tightly coupled scheduling and resource allocation decisions under significant operational complexity. These systems are characterized by high-dimensional, combinatorial decision spaces (e.g., assigning flights to gates, vehicles to multi-service tasks, lockers to dynamic demand, or robotic agents to coupled tasks), where interactions and coordination requirements between entities—such as connecting passengers, pooled service requests, customer time windows, and robotic tasks—often introduce intractable structures. At the same time, decision-makers must balance multiple, often conflicting objectives across stakeholders, including efficiency, reliability, and equity, while accounting for dynamic and stochastic demand patterns. The project addresses these challenges through a combination of advanced optimization methods (e.g., flow-based models that strengthen tractability, decomposition methods), learning-enhanced approximations (e.g., embedding-based representations of complex interactions, passenger flow estimation using generative techniques), and artificial intelligence (e.g., AI-powered digital twin simulations). Together, these approaches enable scalable, real-time decision-making in complex environments, while explicitly capturing trade-offs between operational performance and user-centric outcomes, such as passenger experience, system utilization, and service responsiveness.

The SMART-T7 team is led by Professors Alexandre Jacquillat, Jinhua Zhao, Hamsa Balakrishnan, Amedeo Odoni, and Jason Jackson from MIT, and Professor Hai Wang from Singapore Management University.

The successful candidate will work closely with Professors Alexandre Jacquillat (MIT), Hai Wang (Singapore Management University) and Bo Lin (National University of Singapore). The broad objective of the research will be to harness the power of operations research, AI, data science, and other disciplines to enhance the efficiency and effectiveness of human-machine systems. The primary application areas are smart city operations and robotic fleet management. The research will work at the interface of large-scale optimization, data-driven decision-making, the AI-optimization interface, and digital twin simulation. We invite applicants who hold or about to get a doctoral degree in Operations Research, Computer Science, Artificial Intelligence, Data Science, Industrial Engineering, or other related disciplines. We particularly welcome candidates with expertise and experience in the integration of AI and decision-making:

Key Responsibilities

• Collaborate with the project team and other researchers to design, implement, and evaluate research projects.
• Publish research results in top-tier journals and conferences and disseminate research findings through presentations and other means.
• Mentor graduate and undergraduate researchers involved in related projects.
• Assist with grant writing, project management, and administrative research duties.
• Perform other duties as needed. 

Requirements

• Ph.D. in Operations Research, Computer Science, Artificial Intelligence, Data Science, Industrial Engineering, or other related disciplines by the start of the appointment.
• Expertise 1: Experience with general methods in decision-making under uncertainty, including integer and combinatorial optimization, stochastic and robust optimization, dynamic programming, large-scale optimization, and simulation-based optimization; and/or
• Expertise 2: Experience with general methods in artificial intelligence and machine learning, including reinforcement learning, deep learning, generative AI, multimodal AI, and LLM.
• Experience in the integration of artificial intelligence and decision-making.
• Strong publication record in top-tier conferences and journals.
• Excellent communication and collaboration skills.

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

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

Senior Research Nurse

• Office Location: Buona Vista, Singapore
• Working Hours: Morning/Noon Shift (45 hours per week)
• Monthly Salary: Hourly Rate + Completion Bonus
• Employment Type: Full time, Permanent Contract

Company Overview

The company is a specialized clinical research unit based in Singapore, focusing on early‑phase human trials and innovative health technologies. It integrates biomedical expertise with modern digital tools to advance drug development and support global healthcare progress.

Responsibility

• Clinical Care & Excellence – Deliver professional care and management of clinical trial participants, ensuring privacy and confidentiality at all times.
• Data & Equipment Handling – Collect, verify, and store trial data accurately; operate biomedical equipment proficiently within the CRU.
• Safety & Emergency Preparedness – Apply biohazard safety precautions and participate actively in Code‑blue drills, leading during real emergencies.
• Screening & Trial Execution – Perform general screening activities and protocol‑related tasks under the guidance of the Study Nurse‑in‑Charge.
• Collaboration & Coordination – Work closely with pharmacists, technologists, and support staff to ensure smooth execution of trial activities and auxiliary services.
• Compliance & Documentation – Adhere to SOPs, GCP, and regulatory requirements; maintain accurate records and demonstrate commitment to training and policy compliance.

Requirement

• Registered with Singapore Nursing Board.
• Minimum 2 years of nursing experience in direct in patient nursing.
• Candidate who can start immediately or within short notice will be preferred

We regret to inform you that only shortlisted applicants will be notified.

Recruit Lync Pte Ltd | EA License Number: 22C1000

Chen Hoe Nam | EA Personnel License: R25158678

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Infectious-Disease-Modelling%29/29829-en_GB/?st=10D7DF6900EEA4DFBE1D5F37204E9A8E4AB59151

We regret that only shortlisted candidates will be notified.

Job Description

Qualifications

● A Ph.D. in a relevant field such as computer science, statistics, epidemiology, computational biology, bioinformatics, biostatistics, machine learning, or a related discipline.
● Strong background in at least one of infectious disease modelling, phylogenetics, or phylodynamics (background in computational statistics or machine learning is optional but highly relevant)
● Proficiency in programming languages (R, Python, C++, Java or Julia).
● Experience with mathematical and statistical methods applied to real-world, public health, and global health problems.
● Excellent written and verbal communication skills, including presenting complex concepts to diverse audiences.
● Demonstrated ability to work effectively in a multidisciplinary team and independently.
● Track record of publications in peer-reviewed journals

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-%28Hydrodynamics-of-Coastal-Structures%29/33191-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The selected Research Fellow (RF) will be responsible to lead and manage research activities relating to the project titled Hydrodynamics of coastal structures. 

Key duties will include conducting offshore centrifuge modelling for Coastal Structures and aiding to supervise research assistants. He/she must also help in ensuring compliance with safety and ethical standards and contributing to the preparation of progress reports and grant documentation.

Job Requirements

•    Possess at least a PHD degree in relevant fields such as Civil Engineering, Ocean Engineering, Fluid Mechanics, Computer Science, or related disciplines. Applied Mathematics, Data Science, Electrical and Electronics Engineering, Earth Sciences, Remote Sensing, and Artificial Intelligence are also well-suited. (More details on PhD requirements can be found at: https://nusgs.nus.edu.sg/scholarships/nus-research-scholarship/)
•    Strong written and spoken communication skills. 
•    Open to fixed-term contract