Total 608 Science / R&D / Research job vacancies in PASIR GUDANG

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-%28Nano-Electronic-Process-and-Devices%29/33223-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

A Research Fellow position is open under the supervision of Prof. Gong Xiao, at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).   The Research Fellow will work closely with the Principal Investigator (PI) on one or more research projects.  The project aims to explore advanced semiconductor electronic devices for future advanced integrated circuits.

Qualifications

1.    Possess a Ph. D Degree in Electrical Engineering with strong knowledge in semiconductor device technology and process. 
2.    Strong knowledge in semiconductor device physics. 
3.    At least 4 years in simulation, fabrication, and testing of semiconductor devices. 
4.    Proficient in simulation software, such as Sentaurus, Spice, matlab, FDTD, etc.
5.    Possess relevant expertise proven through coursework and projects during his/her studies.
6.    At least 3 strong publications as the first authors in top conferences and journals.  
7.    Excellent academic track record from well-recognized universities. Excellent course work with strong academic performance. 
8.    Excellent communication skills as he/she is required to publish and to present results at conferences and journals independently. 
9.    Work well with team and be independent, and be able to balance well between advancing his/her own research and contributing to the larger team’s success. 
10.    Be committed to work effectively and strong desire to make a difference in pushing the frontiers of semiconductor technology. 
11.    Open to Fixed Term Contract.

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-EngineerAssistant-%28Interdisciplinary%29%2C-ChBE/33229-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Positions are available for Research Engineers, Research Assistants, and Ph.D. students in the research group of Prof. Soh Siow Ling, 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 Bachelor’s degree 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%29/33227-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The candidate will work closely with the research team to develop advanced methods in Reinforcement Learning under Uncertainties for Reliable Autonomous Decision-Making in Finance. 

Primary responsibilities will include:
•    Data Management: Utilize proficiency in SQL, NoSQL, and vector databases to collect, clean, and manage data for research projects.
•    Research Assistance: Collaborate on research initiatives focused on decision-making in finance, applying quantitative finance and econometric methodologies to analyze data and develop models.
•    Machine Learning: Apply expertise in reinforcement learning and traditional machine learning algorithms to develop predictive models and optimal strategies.
•    Programming: Utilize skills in Python, TypeScript, and JavaScript, along with frameworks like PyTorch, to implement and test quantitative models.
•    Financial Expertise: Apply knowledge of finance, especially in risk management and equity markets, to contribute valuable insights to research projects.
•    Communicate research outcomes through peer-reviewed publications and other scholarly dissemination channels.

Qualifications / Discipline:

•    PhD in Mathematics/Statistics/CS. 

Skills:
•    Proficiency in reinforcement learning, quantitative finance, risk management, and machine learning.
•    Strong programming skill  in Python, TypeScript, and JavaScript, along with frameworks like PyTorch. 
•    Excellent problem-solving abilities and attention to detail. Strong written and verbal communication skills.

Experience:
•    Strong preference for candidates with peer-reviewed publications, patents, conference presentations, research grants, or industry R&D contributions.

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

By submitting your resume, you consent to the collection, use, and disclosure of your personal information per ScienTec’s Privacy Policy (scientecconsulting.com/privacy-policy).

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Contact you about potential opportunities.

Delete personal data as it is not required at this application stage.

All applications will be processed with strict confidence. Only shortlisted candidates will be contacted.

Carmen Tan Huei Mun | R23115837

ScienTec Consulting Pte Ltd (ScienTec Personnel) |11C5781

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.

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.

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

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Associate-%28Epidemiology-and-Modelling%29/33196-en_GB/?st=8BBC1E9510488D1EBDE40715BA0979C8232077DA

We regret that only shortlisted candidates will be notified.

Job Description

The Saw Swee Hock School of Public Health (SSHSPH) at the National University of Singapore (NUS) is seeking multiple determined full-time Research Associate(s) to join a new group led by Dr Angkana T Huang.

Successful candidates will have the opportunity to work on one of several research projects using computational methods to understand the mechanisms underpinning the ecology and evolution of dengue and related arboviruses across Asia and globally. The long-term goal is to generate insights that enable interventions to be better designed, more effectively deployed, and resilient to an ever-evolving infectious disease landscape. Candidates with ambitions to define and pursue independent research questions of mutual interest are strongly encouraged to apply.

Research in the group spans a broad and multidisciplinary scope, for example:

• Macro-processes reshaping who gets infected and when
• The molecular basis of differences in virus properties, such as antigenicity
• Development and validation of computational methods to infer epidemiological quantities

Embedded within the Centre for Epidemic Research and Modelling (CERM) at SSHSPH, researchers will work among a community of motivated, purpose-driven scientists collaborating closely with regional partners and world-leading international collaborators.

Major duties and expectations:
All appointees:
• Conduct and contribute to the design, execution, and interpretation of research projects
• Perform computational analyses, including data processing, modelling, and interpretation of results
• Contribute to the preparation of manuscripts, reports, and presentations
• Participate in team meetings and collaborations with internal and external partners
• Critically appraise evidence and their own results with intellectual honesty, and engages constructively with differing perspectives

Qualifications

All appointees:
• Proficiency in at least one programming language, such as Python or R
• Experience with mathematical or statistical modelling
• Excellent written and verbal communication skills
• Highly organised, with the ability to work effectively both independently and as part of a team

Research Associate:
• Master’s degree or equivalent experience in Epidemiology, Biostatistics/Statistics, Computational Biology/Bioinformatics, Infectious Disease Modelling, or a closely related field

The grade of appointment will be accorded based on qualifications and work experience. Interested applicants are invited to apply directly at our NUS career portal with the documents below. For further enquiries, please contact Dr Angkana T. Huang via huangat@nus.edu.sg.
a. Cover letter highlighting career goals and relevant experience
b. Curriculum Vitae, containing names and contact details of three named referees

We are committed to open science, equitable partnerships, and scientific rigour. Candidates who share these values are strongly 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/Senior-Manager-%28IT-Project-and-Product-Management%29-Faculty-and-Research-Systems/32747-en_GB/

We regret that only shortlisted candidates will be notified.

About NUS IT

NUS Information Technology is the cornerstone to providing reliable, high-performance and secure IT solutions and effective IT governance for the campus. Here at NUS IT, we aim to transform NUS into a borderless computing community providing knowledge at its fingertips by enhancing the use of effective applications and services for teaching and learning.  

We drive a culture that is forward-looking. With a strong passion for IT, our people are always striving to improve, push boundaries and innovate with a "can-do" attitude.  We embrace collaboration, open communication and knowledge sharing. If you see yourself thriving in a dynamic environment and breaking new grounds with innovative ideas, you will find yourself at home in NUS IT.  

As part of our team, you can look forward to an empowered work environment that allows you to take charge of your own career path. We provide competitive remuneration as well as flexible work arrangements to enable your growth and development. We pride ourselves on our diverse workforce and are committed to transforming NUS into a leading global University shaping the future.  

https://nusit.nus.edu.sg/ 

Job Description

You will lead product development, AI delivery, and digital partnership for Faculty and Research systems at NUS. Working closely with faculties, vendors, and cross-functional IT teams, you will translate business needs into technology outcomes that advance NUS' academic and operational goals. This is a hands-on leadership role suited to someone equally comfortable with strategy and delivery.

Duties and Responsibilities

Product Development & Lifecycle Management

• Own the product roadmap for Faculty and Research platforms across the full lifecycle - from discovery and requirements through to delivery, launch, and iteration.
• Develop and maintain a product roadmap aligned with user needs, NUS IT direction, and relevant market developments - engaging regularly with business users and stakeholders to spearhead, gather, clarify, and prioritise requirements into a well-structured product backlog.
• Work cross-functionally with architecture, security, and engineering teams to ensure products are scalable, compliant, and fit for purpose.
• Use prototypes and proof-of-concepts to validate ideas early and reduce delivery risk.
• Drive continuous product improvement through post-launch data analysis and structured user feedback.

AI Solution Delivery

• Identify opportunities where AI can improve processes, enhance user experience, or unlock new capabilities across Faculty and Research domains.
• Translate business needs into clearly defined AI use cases, shaping functional requirements, solution approaches, and measurable success criteria.
• Apply practical understanding of AI approaches - including generative AI, predictive analytics, and workflow automation - to support solution design and implementation.
• Lead end-to-end delivery of AI solutions, from discovery and prototyping through implementation, rollout, adoption, and continuous improvement.
• Drive the design and implementation of agentic workflows and AI-powered automations using orchestration platforms such as n8n, integrating them with enterprise systems, data sources, and business processes where appropriate.

Project Delivery

• Manage end-to-end project delivery - scoping, planning, execution, UAT, and go-live - ensuring targets, quality standards, and NUS governance requirements are met.
• Handle procurement activities including tender preparation, vendor evaluation, and contract management.
• Produce and review project artefacts to ensure compliance with NUS IT policies and audit requirements.
• Coordinate vendors and internal teams to keep delivery on track and within scope.
• Lead and motivate project teams, balancing resource optimisation with team wellbeing.

Strategic Partnership & Faculty Engagement

• Serve as the primary IT account manager for assigned faculties and departments - building trusted relationships with Deans, Heads, and administrative leaders to understand their priorities and co-develop technology plans.
• Align faculty technology needs with NUS IT strategy through bi-annual digital planning cycles, ensuring investments are well-prioritised and outcomes are tracked.
• Facilitate faculty digitalisation efforts by identifying opportunities, championing adoption of new tools, and supporting change management on the ground.
• Represent faculty interests in university-wide IT governance and planning forums.
• Conduct regular service and strategic reviews with stakeholders to ensure IT remains responsive and forward-looking.

Operations & Continuous Improvement

• Oversee application maintenance and support for Faculty systems, ensuring SLAs are consistently met and issues are resolved efficiently.
• Drive a proactive operations model - using data and system analytics to identify trends and address issues before they escalate.
• Collaborate with faculty partners on enhancement prioritisation, progressively automating routine processes to free capacity for higher-value work.
• Manage vendor performance with accountability, ensuring support obligations are met and improvement opportunities are acted on.
• Ensure ongoing compliance with audit, security, and data governance requirements.

Qualifications

• Degree in Information Technology, Computer Science, Computer Engineering, or equivalent.
• At least 10 years of IT experience, including 3+ years in a technical role and 7+ years in project or product management.
• Strong grasp of modern IT technologies, methodologies, architectures, and best practices.
• AI FluencyHands-on experience delivering AI or data-driven initiatives in a complex, multi-stakeholder environment.Practical understanding of modern AI concepts - including generative AI, agentic AI, and predictive/machine learning approaches.Relevant AI certifications, hands-on experience with AI platforms/orchestration tools, or demonstrated continuous learning in the AI domain will be an advantage.

• Strong analytical and communication skills — able to engage credibly with both technical teams and senior business stakeholders. The ability to understand the business questions that users are trying to answer is essential.
• Self-driven, organised, and comfortable managing multiple workstreams with competing priorities.
• PMP, CITPM, or CSPO certification is an advantage.
• Certifications in AI are highly preferred and will be considered an added advantage.
• Experience in the higher education sector is a bonus.