Total 545 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-%28Digital-Concrete%29/32505-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Department of Civil & Environmental Engineering (CEE) of the National University of Singapore is hiring one Research Fellow (RF) to assist the Principal Investigator in the research area of digital concrete with a focus on the design, printing, testing. 

The RF is required to work on : 

(1) Development of durable construction materials from locally available resources for marine applications, 
(2) Assessment of environmental impact of the developed concrete mixture 
(3) Evaluation of the service life of the developed durable concrete mixture. 

Job Requirements

•    Possess a PhD degree in Civil Engineering or Mechanical Engineering with demonstrated experience in designing and conducting experiments, statistical data analysis and possess excellent quantitative, and analytical skills. 
•    The ideal candidate is expected to be self-motivated and can work in an interdisciplinary environment.
•    Ability to work with minimal supervision, plan and perform experimental and field work, and present results in group meetings. 
•    Strong written and spoken communications skills.
•    Prior experience in digital concrete, design, low-carbon concrete is essential to the posted job.  
•    Applications should include (i) a motivation letter, (ii) a detailed Curriculum Vitae, and (iii) contacts of 3 referees. Only shortlisted applicants will be contacted.
•    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-Fellow-%28LLM-for-Construction-Safety%29/32518-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Department of Civil and Environmental Engineering at the National University of Singapore (NUS) is seeking a highly motivated and talented Research Fellow (RF) to join a groundbreaking, government-funded research project: MIDAS. This project aims to transform Design for Safety (DfS) in the construction and built environment sectors by developing an advanced, AI-driven advisory platform. MIDAS will leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multimodal data (text, images, and Building Information Models) to proactively identify design risks and recommend mitigation measures throughout a project's lifecycle. 

The successful candidate will play a pivotal role in driving the core technical development of the MIDAS platform, specifically focusing on multimodal data ingestion and the RAG-based LLM reasoning engine. Key responsibilities include designing the algorithms, collaborating closely with multidisciplinary teams, and leading groups of student interns. 

Job Requirements

•    At least a PhD in Civil Engineering, Built Environment, Computer Science or related field from a reputable university.
•    Evidence of strong publication record in top academic journals. 
•    Proficiency in programming languages, particularly in Python or Matlab for automation and data analysis tasks
•    Proven experience working with Large Language Models and building RAG architectures.
•    Familiarity with BIM, IFC and graph databases.
•    Familiarity with Computer Vision techniques.
•    Strong research experience, specifically in past research projects related to robotics or scenegraphs is required
•    Strong written and oral communication skills.
•    Open to fixed term contract. 

Job Responsibilities:

• Lead and contribute to advanced research efforts in 6G wireless communication technologies.
• Develop and refine technical proposals for international standards organizations (e.g., 3GPP).
• Analyze emerging trends and integrate cutting-edge concepts (e.g., AI, energy efficiency, satellite communications) into research agenda.
• Collaborate with interdisciplinary teams to evaluate technology feasibility and alignment with global standards.
• Drive ecosystem engagement by participating in global alliances, industry forums, and standardization committees.
• Mentor junior engineers in the standardization process and technical writing.

Requirements:

• MS or PhD in Electrical Engineering, Communication Engineering or related field.
• Expert knowledge of digital signal processing, wireless communication algorithms, or protocol design.
• Deep familiarity with mobile communication standards (3G, 4G, 5G and beyond).
• Strong experience in submitting and defending proposals in international standardization bodies.
• Programming skills (C/C++, Matlab, Python) are highly desirable.
• Solid industry track record and with 8 years relevant industry experience, ideally including patenting or published contributions to wireless standards.
• Preferred expertise in at least one area: AI for communications, satellite systems, or wireless energy engineering.

Interested candidates may apply through the application system. We regret that only shortlisted candidates will be notified.

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Job Description

• Lead and contribute to advanced research efforts in 6G wireless communication technologies.
• Develop and refine technical proposals for international standards organizations (e.g., 3GPP).     
• Analyze emerging trends and integrate cutting-edge concepts (e.g., AI, energy efficiency, satellite communications) into research agenda.        
• Collaborate with interdisciplinary teams to evaluate technology feasibility and alignment with global standards.        
• Drive ecosystem engagement by participating in global alliances, industry forums, and standardization committees.        
• Mentor junior engineers in the standardization process and technical writing.

Job Requirements

• MS or PhD in Electrical Engineering, Communication Engineering or related field.        
• Expert knowledge of digital signal processing, wireless communication algorithms, or protocol design.        
• Deep familiarity with mobile communication standards (3G, 4G, 5G and beyond).       
• Strong experience in submitting and defending proposals in international standardization bodies.        
• Programming skills (C/C++, Matlab, Python) are highly desirable.
• Solid industry track record, ideally including patenting or published contributions to wireless standards.
• Preferred expertise in at least one area: AI for communications, satellite systems, or wireless energy engineering.

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-%28Comparative-Effectiveness-and-Real-World-Data-Analytics%29/32515-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 Associate (Comparative Effectiveness and Real-World Data Analytics)

Position Summary
The Centre for Health Intervention and Policy Evaluation Research (HIPER) (https://hiper.nus.edu.sg/) at the Saw Swee Hock School of Public Health (SSHSPH), NUS, is seeking to hire a researcher with a relevant Master’s degree to lead Phase III of the RODEO project, focusing on comparative analyses using oncology real-world data. The candidate will be responsible for designing and conducting comparative effectiveness studies across multiple myeloma, non-small cell lung cancer, and ovarian cancer using structured and processed unstructured data from electronic medical records.

The role is particularly suited to candidates with training in biostatistics, epidemiology, health services research, health economics, public health, data science, or a related field, and who have experience working with observational healthcare datasets.

Key Responsibilities:
• Lead the design and execution of comparative effectiveness analyses using real-world oncology data
• Develop study protocols and statistical analysis plans for observational cohort analyses
• Apply appropriate methods to address confounding, selection bias, missing data, and other threats to internal validity in real-world studies
• Conduct analyses using methods such as propensity score matching, inverse probability weighting, direct covariate adjustment, difference-in-differences, instrumental variables, and survival analysis
• Perform time-to-event analyses, including overall survival and progression-related outcomes
• Support partitioned survival analyses and other methods relevant to economic evaluation and health technology assessment
• Work closely with clinicians, health economists, and data scientists to identify clinically relevant treatment comparisons and confounders
• Collaborate with data engineers and analysts to ensure appropriate variable construction and dataset readiness
• Interpret findings in the context of health technology assessment, reimbursement, and policy decision-making
• Prepare technical reports, presentations, manuscripts, and conference abstracts
• Ensure analyses adhere to methodological standards such as STROBE and ISPOR good practice recommendations for real-world evidence studies
• Participate in project meetings with collaborators across NUS, NCIS, NUH, TTSH, NCCS, and other partner institutions

Requirements:
• Experience working with large observational healthcare datasets, registries, or electronic medical records
• Strong knowledge of causal inference and comparative effectiveness methods
• Experience using statistical software such as R, Stata, SAS, or Python
• Familiarity with oncology data, survival analysis, and longitudinal data analysis will be an advantage
• Understanding of health technology assessment, outcomes research, or economic evaluation is desirable
• Strong written and verbal communication skills
• Ability to work independently while collaborating effectively in a multidisciplinary research team

Preferred Attributes:
• Prior experience with real-world evidence generation in oncology
• Familiarity with OMOP common data model, OHDSI tools, or TRUST platform datasets
• Experience translating statistical findings into policy-relevant insights for clinicians, hospital leaders, or HTA agencies
• Interest in contributing to publications and future grant applications

Qualifications

• Master’s degree in Biostatistics, Epidemiology, Public Health, Health Economics, Data Science, Statistics, Health Services Research, or a related discipline

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-%28Maritime-Safety-and-Data-Analytics-%29/32512-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The project will be engaging a Research Fellow to undertake advanced research on AIS-driven multi-vessel interaction analysis, with a particular focus on estimating navigational capacity in restricted and congested waterways (e.g., port approaches, straits, and narrow channels). Leveraging large-scale Automatic Identification System (AIS) datasets, the study will systematically extract vessel trajectories, characterize interaction patterns among heterogeneous vessel types, and identify critical factors influencing traffic flow efficiency and safety. It will further integrate multi-source data, including high-resolution meteorological and oceanographic information (e.g., wind, waves, currents, and visibility), to capture the impact of environmental conditions on vessel behavior and waterway capacity. Advanced data processing pipelines will be developed to handle massive, noisy, and heterogeneous datasets, ensuring data quality, scalability, and computational efficiency.

The selected RF will be required to collaborate closely with project team members on a range of activities:
(1) Large AIS data process
(2) AIS data based maritime safety assessment 
(3) Capacity estimation for the restricted waters
(4) Preparation of technical reports and slides
(5) Engagement with stakeholders through meetings and discussions.

Job Requirements

• Possess a PhD in Maritime Safety, Computer Engineering/Science, Data Science related subjects (incl. PhD to be received in 6 months after starting work).
• Experience in developing AIS data-driven models.
• Ability to sophisticatedly use at least one programming language, e.g., Python, R Java, SQL, Julia, C# and C++.
• Excellent interpersonal and communication skills.
• Values teamwork and display great leadership. Able to self-manage and self- motivated, with minimum supervision. 
• Open to fixed-term contract.
      
Prioritized Requirements:
• AIS Data mining and analysis, machine learning skills.
• Research experience on maritime risk assessment and big AIS data processing.
• Good publication record in international leading 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-%28Traffic-safety-and-data-analytics%29/32494-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

A few Research Fellows (RFs) will be engaged in a research project to develop a robust, data-driven, and AI-powered framework for evaluating the impact of vehicle speed management policies, with a particular focus on age-related vulnerability. The proposed approach will explicitly account for the age profiles of road users, multiple vehicle types (e.g., passenger cars, trucks, and buses), as well as roadway and environmental conditions.The project aims not only to deepen the understanding of how age and vehicle speed jointly influence crash frequency and injury severity, but also to deliver practical tools to support the design of inclusive and adaptive speed management policies for an ageing population. In addition to utilizing road crash data, the project will also collect and incorporate driving simulator data to support model development and validation.

The selected RF will be required to collaborate closely with project team members on a range of activities:

•    Traffic safety related data collection such as large-scale driving simulator experiments
•    AI-based traffic safety modelling and analysis, 
•    preparation of technical reports and slides, 
•    engagement with stakeholders through meetings and discussions.

Job Requirements

•    Possess a PhD in Traffic Safety, Computer Engineering/Science, Data Science related subjects (incl. PhD to be received in 6 months after starting work).
•    Experience in developing driving simulator-based models.
•    Ability to sophisticatedly use at least one programming language, e.g., Python, R Java, SQL, Julia, C# and C++.
•    Excellent interpersonal and communication skills.
•    Good teamwork and leadership, self-manage and motivated, with minimum supervision. 
•    Open to fixed-term contract.
    
Prioritized Requirements:

• driving simulator-based model development, machine learning skills.
• Research experience on traffic safety and driving simulator usage.
• Good publication record in international leading 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-%28Traffic-safety-and-data-analytics%29/32493-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

A few Research Fellows (RFs) will be engaged in a research project to develop a robust, data-driven, and AI-powered framework for evaluating the impact of vehicle speed management policies, with a particular focus on age-related vulnerability. The proposed approach will explicitly account for the age profiles of road users, multiple vehicle types (e.g., passenger cars, trucks, and buses), as well as roadway and environmental conditions.The project aims not only to deepen the understanding of how age and vehicle speed jointly influence crash frequency and injury severity, but also to deliver practical tools to support the design of inclusive and adaptive speed management policies for an ageing population. In addition to utilizing road crash data, the project will also collect and incorporate driving simulator data to support model development and validation.

The selected RF will be required to collaborate closely with project team members on a range of activities:

•    Traffic safety related data collection such as large-scale driving simulator experiments
•    AI-based traffic safety modelling and analysis, 
•    preparation of technical reports and slides, 
•    engagement with stakeholders through meetings and discussions.

Job Requirements

•    Possess a PhD in Traffic Safety, Computer Engineering/Science, Data Science related subjects (incl. PhD to be received in 6 months after starting work).
•    Experience in developing driving simulator-based models.
•    Ability to sophisticatedly use at least one programming language, e.g., Python, R Java, SQL, Julia, C# and C++.
•    Excellent interpersonal and communication skills.
•    Good teamwork and leadership, self-manage and motivated, with minimum supervision. 
•    Open to fixed-term contract.
      
Prioritized Requirements:

• driving simulator-based model development, machine learning skills.
• Research experience on traffic safety and driving simulator usage.
• Good publication record in international leading 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-%28Construction-Robotics%29/32520-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Department of Civil and Environmental Engineering at the National University of Singapore (NUS) is seeking to recruit a Research Fellow (RF) to participate in innovative general research focused on robotics and automation within the construction and built environment. 

The successful candidate will play a key role in developing an algorithmic solution for robotics that integrated with Building Information Modeling (BIM). Key responsibilities include designing the software architecture, applying advanced robotics techniques to support project objectives, collaborating closely with multidisciplinary teams, and leading groups of student interns. In addition to project-specific research tasks, the Research Fellow will be expected to handle administrative and operational matters related to the Centre for Construction Robotics & Automation (CCRA). 

Job Requirements

•    At least a PhD in Mechanical Engineering with a specialization in Robotics, or related field from a reputable university.
•    Evidence of strong publication record in top academic journals.
•    Proficiency in programming languages, particularly in Python or Matlab for automation and data analysis tasks.
•    Prior Civil Engineering/Built Environment related experience, practices and workflows will be an added advantage.  
•    Strong research experience, specifically in past research projects related to robotics or scene graphs is required.
•    Strong written and oral 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/Senior-Research-Fellow-%28Infectious-Disease-Modelling-&-AI-for-Public-Health%29/32500-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

About the Role
The Centre for Epidemic Response & Modelling (CERM) at NUS Saw Swee Hock School of Public
Health invites applications for a Senior Research Fellow to help lead a vibrant, internationally
connected research programme spanning Bayesian infectious disease modelling, AI-driven
epidemic forecasting, genomic epidemiology, and pandemic preparedness. The postholder will
work with Asst. Prof. Swapnil Mishra (Deputy Director, CERM and AI for Public Health Programme)
and engage an active network of collaborators spanning CERM, NUS, Imperial College London,
Ashoka University, the Communicable Diseases Agency Singapore (CDA), the National
Environment Agency Singapore (NEA), the Machine Learning & Global Health Network (MLGH),
and wider regional and global partners.
This is a senior scientific role with significant autonomy. The successful candidate is expected to
drive independent research streams, provide intellectual leadership across multiple concurrent
grants, and mentor junior researchers. The portfolio spans methodological innovation and applied
public health impact, including real-time surveillance platforms, lineage transmissibility models, AIpowered
decision-support tools, and equitable AI for Public Health in Asian settings.

Key Responsibilities
• Lead and independently execute high-impact research across one or more of the group's
active programmes: Bayesian genomic-epidemiological modelling, AI for epidemic
forecasting, and arbovirus genomic surveillance.
• Design novel statistical and computational methodologies and publish them in leading
journals and present at international conferences.
• Provide scientific leadership and day-to-day mentorship to Research Fellows, Research
Associates, and Research Assistants.
• Take a leading role in grant writing, progress reporting, and engagement with funding
agencies and public health partners.
• Represent the group at national and international conferences; build and sustain
collaborative networks.
• Contribute to curriculum and teaching support for relevant graduate courses at SSHSPH.

Additional Opportunities
The group actively supports career development through conference travel, training workshops, and mentorship from senior researchers and international collaborators.

Qualifications

• PhD in statistics, biostatistics, computational biology, epidemiology, computer science, or a
closely related discipline.
• Minimum of two years of postdoctoral experience.
• Demonstrable expertise in Bayesian inference and probabilistic modelling; experience with
Stan, PyMC, NumPyro, Turing, or equivalent PPLs.
• Strong track record of publications in peer-reviewed journals commensurate with career stage.
• Proficiency in Python and/or R; familiarity with high-performance and cloud computing environments.
• Experience in at least two of: phylodynamics / genomic epidemiology, deep learning for sequence or tabular data, reinforcement learning, spatial modelling, or real-time nowcasting.
• Demonstrated ability to supervise junior researchers and contribute substantively to grant applications.
• Excellent written and oral communication skills; ability to engage clinical, public health, and policy audiences.

Interested applicants should submit the following documents:
• A cover letter explaining your interest in the position, relevant experience, and research vision.
• A comprehensive curriculum vitae, including a full list of publications.
• A research statement (maximum two pages) outlining past contributions and future directions.
• Contact information for two professional references (letters may be requested).

Review of applications begins immediately and continues until the position is filled. The anticipated start date is flexible by negotiation.

Responsibilities

• Develop, implement, and validate autonomous berthing algorithms for MASS, integrating vessel manoeuvring models, sensor data, and environmental disturbances (wind, waves, currents).
• Contribute to the simulation and digital twin platforms for autonomous berthing operations, including real-time control system integration.
• Support physical model-scale experiments in the TCOMS ocean basin, focusing on berthing manoeuvres and control refinement.
• Collaborate with industry partners, and technology providers to address operational, safety, and regulatory requirements for autonomous berthing.
• Participate in preparing project deliverables, proposals, and publications under funded research programmes.
• Perform other tasks as assigned by the supervisor.

Requirements

• Bachelor/Master in Naval Architecture, Maritime Engineering, or related field.
• Experience in autonomous vessel control, motion planning, and manoeuvring dynamics with constrained environments.
• Strong programming skills in MATLAB/Simulink, Python, or C++, with exposure to real-time control.
• Strong analytical ability, creativity, and interest in real-world R&D challenges.
• Good teamwork and communication skills to engage with multidisciplinary stakeholders.
• Independent, resourceful, and able to deliver under tight schedules.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

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-Engineer-%28Digital-Concrete%29/32504-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Department of Civil & Environmental Engineering (CEE) of the National University of Singapore is hiring one Research Engineer (RE) to assist the Principal Investigator in the research area of digital concrete with a focus on the design, printing, testing. 
 

The RE is required to work on:
(1) Development of durable construction materials from locally available resources for marine applications.
(2) Assessment of environmental impact of the developed concrete mixture.
(3) Evaluation of the service life of the developed durable concrete mixture. 

Job Requirements

·     Possess a bachelor’s degree in civil engineering or mechanical engineering with demonstrated experience in designing and conducting experiments, statistical data analysis and possess excellent quantitative, and analytical skills. 
•    The ideal candidate is expected to be self-motivated and can work in an interdisciplinary environment. 
•    Ability to work with minimal supervision, plan and perform experimental and field work, and present results in group meetings. 
•    Strong written and spoken communication skills. 
•    Prior experience in digital concrete, design, low-carbon concrete is essential to the posted job.  
•    Open to fixed-term contract. 
•    Applications should include (i) a motivation letter, (ii) a detailed Curriculum Vitae, and (iii) contacts of 3 referees. Only shortlisted applicants will be contacted.
•    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-Engineer-%28LLM-for-Construction-Safety%29/32519-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Department of Civil and Environmental Engineering at the National University of Singapore (NUS) is seeking a highly motivated and talented Research Engineer to join a groundbreaking, government-funded research project: MIDAS. This project aims to transform Design for Safety (DfS) in the construction and built environment sectors by developing an advanced, AI-driven advisory platform. MIDAS will leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multimodal data (text, images, and Building Information Models) to proactively identify design risks and recommend mitigation measures throughout a project's lifecycle. 

The successful candidate will play a pivotal role in assisting with the core technical development of the MIDAS platform, specifically focusing on multimodal data ingestion and the RAG-based LLM reasoning engine. Key responsibilities include designing the algorithms, collaborating closely with multidisciplinary teams, and leading groups of student interns. 

Job Requirements

•    At least a bachelor’s in Civil Engineering, Built Environment, Computer Science or related field from a reputable university. Masters will be preferred.
•    Evidence of strong publication record in top academic journals
•    Proficiency in programming languages, particularly in Python or Matlab for automation and data analysis tasks
•    Familiarity working with Large Language Models and building RAG architectures.
•    Familiarity with BIM, IFC and graph databases.
•    Strong research experience, specifically in past research projects related to robotics or scene graphs is required
•    Strong written and oral 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-Engineer-%28Development-of-Silicon-Photonics-Technology%29/32496-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Singapore Hybrid Integrated Next-Generation µ-Electronics (SHINE) research centre in National University of Singapore (NUS) is looking for applicants for a Research Engineer position in the area of Silicon photonic technologies.
The candidate will work closely with Researchers and Professor to
support the design, development, and evaluation of next-generation photonic systems. This includes translating simulated results into physical test vehicles and deriving insights through experimental work and data analysis.

Responsibilities will include:

1.    Conduct laboratory work involving simulation, fabrication, and characterization of photonic chips and devices.
2.    Basic data processing including analysis, correlation, troubleshooting, and presentation of experimental and simulation results.
3.    Conduct literature reviews to maintain awareness of recent advances in related photonic and interconnect technologies.
4.    Maintain accurate and detailed records of research activities, methodologies, and results.
5.    Collaborate with other engineers, scientists, and researchers to achieve project goals.
6.    Assist in equipment purchase, commissioning, and ownership.

Qualifications

•    A degree or higher degree in Electrical Engineering, Electronics, Physics, or related Science disciplines from a reputable University/Institute, or equivalent relevant experience. 
•    Passion in microelectronics or optoelectronics.
•    Candidate with experience in with Lumerical and/or Zemax simulation software is preferred.
•    Knowledge on programming skills (e.g. Python, MATLAB
•    Good communication skills, including scientific writing and presentation
•    Ability to work independently and collaborate within a diverse team.
•    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-ENGINEER-%28LOGISTICS-&-SUPPLY-CHAIN-OPTIMIZATION%29/32506-en_GB/

We regret that only shortlisted candidates will be notified.

The Role

Are you passionate about solving complex logistics and supply chain challenges through cutting-edge modeling, simulation, and data science?

The Logistics Institute – Asia Pacific (TLI-AP), a university-level research institute at the National University of Singapore is seeking a Research Engineer to join our dynamic team and contribute to innovation that drive operational excellence.

As a Research Engineer, you will:

• Design, build, and implement optimization models tailored to transportation and logistics contexts.
• Develop and refine custom heuristics and metaheuristics (e.g., Tabu Search, Genetic Algorithms) to solve large-scale, real-world problems.
• Utilize commercial and open-source solvers such as Gurobi, CPLEX, and Google OR-Tools.
• Deliver simulation-based data science solutions using tools like AnyLogic, AnyLogistix, FlexSim, Arena, and Demo 3D.
• Analyze historical and real-time data to uncover insights and support decision-making.
• Apply data-cleaning techniques and statistical analysis to understand complex datasets.
• Create compelling visualizations using MS Power BI and Tableau.

Requirements

• Bachelor or Master degree in Industrial Engineering, Operations Research, Computer Science, or a related field.
• Those with 1–2 years of experience in logistics and supply chain management is an advantage. Those without relevant work experience but who have the technical skills are welcome to apply.

• Proficiency in Python or similar programming languages and SQL.
• Experience with optimization tools (Gurobi, CPLEX, OR-Tools).
• Familiarity with simulation platforms (AnyLogic, FlexSim, Arena, AIMMS, Demo 3D).
• Skilled in data visualization tools (MS Power BI, Tableau).
• Strong command of MS Office Suite

Location: NUS Kent Ridge Campus, Singapore

Ready to make an impact? Apply now and be part of a team that’s shaping the future of logistics and supply chain innovation.

Interested applicants can submit their CV to the NUS Career Portal