Total 460 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-Assistant-%28Pharmacy-and-Pharmaceutical-Sciences%29/32592-en_GB/?st=F60B62FB7157CB4DA8743736577FB0031852900E

We regret that only shortlisted candidates will be notified.

Job Description

The successful candidate will work with Dr. Boxiang Liu on the wetlab validations of AI-optimised mRNA sequences for stability and protein expression.

The main responsibilities of the position include:
- Gene synthesis and in vitro mRNA transcription for transfection into cells.
- Cell line construction and maintenance.
- Analysis of protein expression by flow cytometry.
- High throughput sequencing of gene libraries.
- Characterisation of mRNA vaccine and therapeutic effects in vivo.

Qualifications

Qualifications / Discipline:
- Bachelor’s or Master's degree in molecular biology, cell biology, immunology, or a related discipline; equivalent research experience will also be considered.  

Skills: 
- Proficiency in PCR, cloning, mammalian cell culture and transfection, fluorescence microscopy and immunostaining is required.
- Experience with fluorescence-activated cell sorting and flow cytometry data analysis, in vitro transcription, high throughput gene library construction and sequencing, and mouse model perturbation and analysis is advantageous.
- Excellent self-motivation, teamwork skills, and the ability to design and troubleshoot experiments are preferred.

Experience: 
- Prior laboratory experience in molecular biology, cellular biology or immunology projects with mammalian cell experiments.
- Experience with in vivo experiments, particularly with mouse models, is an advantage.
- Contribution to at least one paper in a relevant field. Having a published first author paper is an advantage.

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Assistant-Manager-Manager%2C-Research-Admin-&-Programme-Management/32575-en_GB/

We regret that only shortlisted candidates will be notified.

Position Summary

The candidate will play an important role in driving research administrative excellence, managing research collaborations and grants in Operations Research and Analytics (ORA) at IORA. This role will be the key administrative point of contact for research teams, partners, and stakeholders, and will lead process improvements across research and programme management functions.

Key Responsibilities

1. Research Administration, Collaboration & Grant Management

• Lead and oversee research administration activities within IORA, ensuring robust processes for research collaborations, industry partnerships, and compliance with NUS and funding agency requirements.
• Drive and coordinate research grant applications: Advise and support PIs and research teams in grant identification, application preparation, internal reviews, timely submission, and post-award administration.
• Monitor and manage grant portfolios: Oversee financial tracking, milestone monitoring, progress reporting, and compliance for all active research grants and collaborative projects.
• Serve as the primary administrative liaison with academic, industry, and funding partners for research collaborations, ensuring effective communication, documentation, and issue resolution.
• Supervise procurement, HR administration, and claims related to grant-funded activities; optimise processes for onboarding research staff, faculty, and students.
• Maintain oversight of research records, partnership agreements, and audit documentation for internal and external reporting.

2. Operations and Event support

• Organise event and seminar planning for IORA, including industry engagement events, workshops, and research seminars, ensuring effective resource allocation and logistics.
• Drive process improvements and digital transformation in research administration and programme management functions.

4. Leadership, Reporting & Compliance

• Compile, review, and submit management reports on research activities, grants and compliance for audits and strategic planning.
• Champion best practices in research integrity, data management, and regulatory compliance across all administrative processes.
• Represent IORA in meetings with internal and external stakeholders on matters related to research administration, grants, and postgraduate programmes.

Qualifications and Requirements

• Bachelor’s degree, preferably with further professional qualifications in research administration, business, or higher education management.
• At least 7 years’ relevant experience, with proven expertise in research administration, grant management, and postgraduate programme operations (ideally within a university or research institute).
• Strong leadership, interpersonal, and communication skills, with experience supervising staff and managing cross-functional teams.
• Excellent organisational, analytical, and problem-solving abilities.
• Demonstrated ability to drive process improvements and manage complex projects.
• Proficient in the use of research administration systems, grant portals, and office software

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-%28LWIR-Perception-&-UAV-State-Estimation%29/32576-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

A Research Engineer position is open at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).

The Research Engineer will work closely with the Principal Investigator (PI) on the project on Long-Wave Infrared (LWIR) Imaging for Autonomous Navigation. The position focuses on developing robust perception, state estimation, and odometry algorithms using LWIR (thermal) imaging for UAVs operating under degraded visual conditions, such as low illumination, smoke, fog, and texture-sparse environments.

The Research Engineer will design and implement LWIR-based odometry and thermal-inertial state estimation frameworks, including multi-sensor fusion with IMU and other onboard sensors. The work will involve both model-based approaches (e.g., filtering and optimization-based estimation) and learning-enhanced methods for improving robustness and generalization across environments.

The candidate will also be responsible for system integration and real-world deployment on UAV platforms, including embedded implementation, sensor calibration, and experimental validation in both indoor and outdoor scenarios. The developed methods will be evaluated in realistic navigation tasks under challenging environmental conditions.

The initial appointment duration is 12 months, which can then be extended based on an evaluation at the end of the initial appointment.

The candidate should have a Bachelor’s degree from a reputable university, with expertise in robot perception, state estimation, or aerial robotics.

A successful candidate should have a strong mathematical background (e.g., linear algebra, optimization, probability, stochastic processes), along with demonstrated experience in state estimation, odometry, or SLAM systems, particularly in robotics applications.  

Qualifications

•    Possess min a Bachelor’s degree in Computer Engineering/Science or related disciplines (e.g., Electrical Engineering, Mechanical Engineering, Mathematics).
•    Have research experience in robot perception, state estimation, SLAM, or sensor fusion.
•    Experience with thermal (LWIR) imaging, event cameras, or other non-RGB sensing modalities is highly preferred.
•    Familiar with visual-inertial odometry (VIO), thermal-inertial odometry, or multi-sensor fusion frameworks.
•    Knowledge of state estimation techniques, including EKF, UKF, factor graph optimization, or moving horizon estimation (MHE).
•    Experience with feature extraction or direct methods under low-texture or low-SNR conditions is a plus.
•    Proficient in C++ or Python; experience with ROS and real-time robotic systems.
•    Familiar with UAV systems (e.g., PX4), and simulation environments such as Gazebo or AirSim.
•    Experience in sensor calibration (intrinsic/extrinsic) and time synchronization is desirable.
•    Strong analytical and problem-solving skills, demonstrated through relevant publications or projects.
•    Ability to deploy algorithms on embedded platforms (e.g., NVIDIA Jetson) is a plus.
•    Excellent communication skills for publishing and presenting research outcomes.
•    Experience in world-class research environments is highly valued. 
•    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-%28Dept-of-O&G%29/32559-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Job Description

The National University of Singapore invites applications for one highly motivated Research Fellow specializing in Biostatistics and Epidemiology in the Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine. A/Prof Chan Shiao-Yng’s (obgchan@nus.edu.sg) team conducts research in understanding the impact of maternal and environmental factors on placental and offspring development, and implications for the developmental origins of health and disease (DOHaD). The appointment will be for 1 year in the first instance, with the possibility of extension to 3 years depending on progress and available funding.

Purpose of the post

We are seeking highly motivated PhD graduates with expertise in Biostatistics and Epidemiology, and preferably some background experience in Molecular Biology and Physiology. Candidates should have an interest in endocrinology, pregnancy and in-utero development. The successful candidate will help to design and conduct studies, analyse data, write papers and grants/reports, and present findings at meetings.

Main Duties and Responsibilities

The successful candidate should be able to:

(1) employ basic and advance biostatistical and bioinformatic methods to analyse data from mother-offspring cohorts and randomised controlled trials

(2) write original research articles/reviews, write grants/reports, prepare presentation materials and disseminate findings

(3) provide administrative support to research projects, such as organizing meetings, maintaining regular communication with other members of the research team, supervising more junior team members, and collaborate with other external study sites

(4) collaborate with team members in the day-to-day running of projects, including assisting with sample/data collection (whenever relevant/necessary)

(5) maintain the highest standard of professional conduct and record keeping in accordance with policies and procedures;

(6) assist with any other duties of a similar nature that are delegated by the PI.

Qualifications

The candidates are required to demonstrate that they

(a) have the relevant scientific understanding and experience;

(b) have a proven track record in research in the form of publications in top English language journals;

(c) have the ability to communicate in good written and spoken English;

(d) are able to work independently and in a team, have an investigative mindset, attention to detail, and good leadership ability;

Remuneration will be commensurate with the candidate’s qualifications and experience.

Please submit your application supported by a detailed CV (indicating current/expected salary, including personal particulars, academic and employment history, and complete list of publications/oral presentations, information on years of experience in research & laboratory work and full contact information of 3 referees).

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

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Advanced-Instrumentation%29/32587-en_GB/?st=2B0997AD31DA7AB45CFACB8BAFF892A06C5E5FE2

We regret that only shortlisted candidates will be notified.

Job Description

The job holders are to work with PI and the research team to operate, maintain high-end and general instrument and field studies to study air quality in urban environment. 

Qualifications

·  PhD in Science / Engineering / Aerosol & Air quality sciences or related discipline

·  Leading operation, maintenance, troubleshooting and data analyses of advanced instruments of ACSM, AMS, PTR-MS, etc.

·   Handling and analyzing data

·   Planning and conducting field studies

·   Proficient in technical presentation, slide making, report writing, etc.

·   Experiences in journal publications and proposal writing

·   Proven rounded and effective team player with strong initiative and ownership of the research project

Job Description & Requirements

Chugai Pharmabody Research Pte. Ltd. (“CPR”) was established in Singapore as a wholly-owned subsidiary of Chugai Pharmaceutical Co., Ltd (Chugai), a member of Roche group, in January 2012 and started operations on July 2, 2012. Located at Biopolis in Singapore, it aims to generate new antibody drugs based on Chugai’s proprietary antibody engineering technologies, such as recycling antibody®, sweeping antibody®, bispecific antibody, various Fc engineered antibodies, and other new antibody engineering technologies that are under development.

The Senior Accounts Officer role involves comprehensive financial management responsibilities across four key areas:

Key Responsibilities

Financial Report Preparation

• Maintain accurate and complete accounting records in compliance with current accounting standards
• Execute monthly closing processes

Regulatory and Reporting Compliance

• Assist the team in meeting financial reporting requirements and tax compliance obligations
• Serve as liaison with external stakeholders including auditors, tax agents, and government authorities

Process Improvement

• Analyse and enhance business process efficiency and effectiveness

Accounting System Administration

• Manage user access rights and system configurations

Required Qualifications

Education & Experience

• Bachelor's degree in Accountancy
• Relevant work experience, preferably in Accounts Payable (AP)

Technical Skills

• Strong understanding of local accounting standards and tax obligations
• Experience with SAP B One and SAP S4 Hana systems (preferred)

Personal Attributes

• High attention to detail and strong organizational skills
• Ability to work independently and meet deadlines
• Excellent verbal and written communication abilities

This position offers an opportunity to work in a comprehensive accounting role with both technical and administrative responsibilities, requiring both accounting expertise and system management skills.

Interested applicants are invited to email their detailed resume, qualifications, availability, current and expected salary to: recruitment@chugai-pharmabody.com

For more information regarding our Company, you may refer to our website at: http://chugai-pharmabody.com/

We regret that only short-listed candidates will be notified

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Computational-Chemistry%29/30502-en_GB/?st=DC3A8BC5AE7C20880C78594D9FA30DEC0C8DE875

We regret that only shortlisted candidates will be notified.

Job Description

A postdoc position is available in the Department of Materials Science and Engineering at the National University of Singapore under the direction of Dr. Peichen Zhong. This role involves using computational chemistry and machine learning to model electrochemical systems while collaborating with experimentalists.

Qualifications

• Ph.D. in Computational Chemistry/Physics/Materials Science, or related field (completed by start date).
• Strong oral and written communication skills in English.
• Strong background in statistical mechanics and thermodynamics
• Proficiency in density functional theory calculations (e.g., VASP, Quantum Espresso, Q-Chem, PySCF)
• Proficiency in at least one mainstream deep learning framework (PyTorch or JAX)
• Expertise in atomistic thermodynamic & kinetic simulations in electrochemistry
• Expertise in rare-event sampling, free energy calculation, and reaction network modeling
• Ability to independently design and execute research projects, with a track record of high-quality publications.

Responsibilities

• Responsible for operations, maintenance, engineering aspects of Instrumentation & Control (ELV) systems and insfrastructure. 
• Manage daily operations to ensure systems are operating in optimal conditions.
• Respond to and perform troubleshooting for all system failures or deficiencies.
• Respond to Issues, Complaints and Queries in a timely fashion, keeping relevant stakeholders abreast.
• Plan and manage maintenance activities in accordance to OEM or regulatory requirements.
• Manage vendors/contractors on outsourced services to meet the fulfillment of contract terms and agreement.
• Involvement in facilities related projects such as Facilities Upgrading, Improvement Projects and Tool Hook-Up. Close liaison with consultants, authorities, contractors, stakeholders and etc to ensure seamless and timely completion of projects.
• Prepare RFQ / tender documents for all purchase requests.
• Compliance to EHS and regulatory requirements for all activities carried out.
• Active contribution in energy conservation program and initiatives.

Qualifications and work experiences

• An engineering degree. Diploma / ITE cert holders with many years of relevant working experience may be considered too.
• Min. 3 years of relevant work experience preferably in a wafer-fab or similar industry.
• Good experience in electrical, ELV and building automation systems.
• Project management skills; Familiar with government procurement policies and procedures is a major plus
• Good working knowledge on other facilities for e.g. HVAC, mechanical systems typical in a wafer-fab is a plus.
• Familiar with the local codes from BCA, URA, SCDF/FSB, NEA and other statutory requirements
• Analytical skills to trouble-shoot basic facilities systems.
• Able to work independently

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 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-in-Middle-East-Institute/32511-en_GB/?st=CEC2C77AAA55306C3E1A3D6E86A41CCCF84908B8

We regret that only shortlisted candidates will be notified.

Middle East Institute (MEI)

The Middle East Institute (MEI) is looking for outstanding researchers for the position of Research Fellow.

As a Singapore-based research institute, MEI is well-positioned between the Middle East and East Asia. We are therefore on the look-out for researchers who not only have an in-depth knowledge of the Middle East but also understand Northeast or Southeast Asia.

In particular, we seek researchers with expertise in the following areas of relevance to the Institute’s Research Clusters:

1.    Global and geopolitical dynamics of the Middle East, including China, Iran and Turkey.

2.    Economies of the Gulf states, and the social, religious and cultural reforms they are undergoing.

Job Description

The Institute’s Research Fellows work under the supervision of the Director and Deputy Director. You may therefore be asked to:

1. Participate in current cluster projects and be encouraged to lead a project.
2.  Assist with organising workshops and conferences.
3. Participate in the Institute’s outreach activities.
4. Contribute to academic research via peer-renewed journals, books, and chapters where requested.

As a Research Fellow at MEI, you will be asked to contribute regularly to our publications and other communications platforms. Some activities you can expect to undertake include:

1. Being actively involved in the activities of your chosen research cluster and those of the wider Institute Contributing at least three in-house publications.
2. Write detailed analyses of current events for our stakeholders.
3. Call for, and edit, papers offering in-depth analysis of a single subject, for quarterly publication.
4. Providing short commentaries to our social media platforms.
5. Where appropriate, accepting requests for commentary from local and international media.
6. Participating in our outreach activities.

Job Requirements

1. You must have fulfilled all requirements of securing a PhD from a reputable university.
2. You may apply even if you are still a PhD candidate. If you are successful, your graduation must be confirmed by the time you join the Institute. An official letter from the Registrar’s Office of your university will be required to confirm the award of your PhD degree.

Terms of Appointment

1. The appointment is for two years only.
2. You will be paid a fixed monthly salary. This is an all-inclusive sum of stipends for housing and living expenses.
3. You will receive a one-time travel assistance payment.
4. Housing is NOT PROVIDED. You are expected to make your own private arrangements.
5. All salary and benefits-in-kind are subject to tax as required by Singapore’s tax laws.
6. You will be eligible for support for research fieldwork and conference attendance.
7. For further information on benefits, about working in NUS and living in Singapore, go to 'Why Join Us'.

Application Process

To apply for this position, please combine the following documents in 1 PDF and attach it under the CV column in the NUS Career Portal when submitting your application:

1. Covering Letter;
2. Curriculum Vitae;
3. Copies of Certificates and Degrees (in English);
4. Two samples of published work in English; and
5. Two Letters of Reference

Additional Application Information

1. Only fully completed applications will be considered including the submission of the two letters of reference.
2. Only successful candidates will be notified (via email). If you are not contacted within ten weeks after the closing date of the advertisement, the position has been filled.
3. Appointment is conditional on approval by the National University of Singapore (NUS) and the Ministry of Manpower granting you an Employment Pass or other applicable work passes.

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-AssociateAssistant-%28Infectious-Disease-Modelling-&-AI-for-Public-Health%29/32509-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 is recruiting two Research Associates/Assistants to support a diverse portfolio of research projects at the intersection of infectious disease modelling, Bayesian inference, AI, and public health. Projects span AI-driven epidemic forecasting, transmission modelling in the ASEAN region, social network dynamics and use for large language models for public good. Successful candidates will be embedded in a multidisciplinary team working with epidemiologists, clinicians, biostatisticians, data scientists, and public health agencies.

We welcome candidates with complementary skill profiles. One position is oriented towards computational/statistical modelling; the other towards data engineering, visualisation, and software development. Both positions involve hands-on research work and will suit candidates looking to build a strong research track record before or alongside a PhD. 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.

Key Responsibilities
• Implement and test statistical and computational models for infectious disease dynamics (compartmental models, Bayesian inference, phylogenetic analysis, or machine learning pipelines depending on profile).
• Process, clean, and analyse large-scale epidemiological, genomic, and/or mobility datasets.
• Develop data visualisation tools and contribute to interactive surveillance dashboards.
• Support the preparation of manuscripts, reports, conference presentations, and workshops.
• Collaborate with internal team members and external partners across institutions and countries.
• Contribute to code documentation and reproducible research workflows.

Additional Opportunities
Exceptional candidates may have the opportunity to pursue a PhD at NUS. The group actively supports career development through conference travel, training workshops, and mentorship from senior researchers and international collaborators.

Qualifications

Research Associate (higher band): Master's degree in a relevant discipline (statistics, epidemiology, computer science, bioinformatics, computational biology, biostatistics, or related) with two years of relevant work experience.

Research Assistant (entry band): Bachelor's degree with strong analytical training; candidates with no experience are welcome to apply.

• Solid quantitative background; familiarity with Bayesian inference or machine learning is an advantage.
• Proficiency in Python and/or R; experience with probabilistic programming (Stan, PyMC, NumPyro) or deep learning frameworks (PyTorch, JAX) is desirable but not required.
• Ability to work with real-world datasets and to communicate findings clearly in writing and presentations.
• Demonstrated ability to work both independently and as part of a team.
• A publication or pre-print record (for Research Associate level) is an advantage but not essential.

Interested applicants should submit the following documents:
• A cover letter explaining your interest in the position, and relevant experience,
• A comprehensive curriculum vitae.
• Contact information for two professional references (letters may be requested).

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-%28Environmental-Microbiology-and-Biotechnology%29/32492-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are seeking for a highly motivated and collaborative Research Engineer with demonstrated skills in environmental engineering, microbiome, and bioinformatics. The position involves developing novel biotechnologies for nutrients removal and pollutants detoxification in bioreactors, engineered systems, waterbodies and the environment, in particular cultivation and characterization of functional microbes, predictive understanding of microbiome dynamics and functioning in engineering systems such as bioreactors in lab and pilot scale. The selected Research Engineer will be responsible for sample collection or management, culturing, microbiome analysis, data processing, integration, etc. He/she will also be encouraged to collaborate with other laboratory members on diverse research projects.

Job Requirements

•    Possess a bachelor’s degree in environmental engineering.
•    Master’s degree is preferred. 
•    At least 3 years’ of relevant working experience  
•    Prior research experience in one or more areas such as environmental microbiology and biotechnology, chemical analysis; 
•    Multidisciplinary knowledge and research experience in engineering, chemical analysis, environmental biotechnology, bioinformatics, statistics, data mining, machine learning.
•    Independent, motivated, resourceful and able to work in a team.
•    Strong written and spoken communication skills. 
•    Excellent quantitative, writing, and presentation skills.
•    Experience in publishing peer-reviewed publications.
•    Demonstrated ability to direct and run independent research project(s).
Experience collaborating with industrial teams.
•    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-%28Supply-Chain-Management%29/32507-en_GB/

We regret that only shortlisted candidates will be notified.

Job Role/ Core Capabilities

• Experience with logistics and supply chain processes, including transport operations, fleet management, and operational readiness frameworks
• Model & Algorithm Development: Design, build and implement optimisation models for various transportation contexts, and machine learning classifiers
• Heuristics & Solvers: Develop and refine custom heuristics and metaheuristics (e.g., Tabu Search, Genetic Algorithms) to find high-quality solutions for large-scale, real-world problems. Utilise commercial and open-source solvers (e.g., Gurobi, CPLEX, Google OR-Tools).
• Formulate and solve Mixed-Integer Linear Programmes (MILP) for real-time vehicle–task assignment including objective function design and constraint modelling
• Design, implementation, and delivery of simulation data science solutions to perform system-of-systems discrete event simulations for significantly complex operational processes (e.g., AnyLogic, AnyLogistix, FlexSim, Arena, Demo 3D, etc.)
• Data Analysis & Feature Engineering: Analyse historical and real-time data from multi-source inputs
• Experience analysing large datasets and applying data-cleaning techniques along with performing statistical analyses leading to the understanding of the structure of datasets
• Machine Learning & AI: Train, evaluate, and deploy supervised classification models (e.g., XGBoost, LightGBM), design ensemble pipelines combining rule-based, probabilistic, and ML components; apply explainability tools (e.g., SHAP, LIME) to produce interpretable, auditable decision outputs
• Experience with data visualisation and visualisation tools (e.g., MS Power BI, Tableau), including design and delivery of operational KPI dashboards covering driver–task mismatch rates, fleet health distribution, fatigue heatmaps, and dispatch allocation efficiency

Requirements

Education

• PhD in industrial engineering, Operations Research, Computer Science, Operations Research or an equivalent field

Experience

• Min 1–2 years of experience in logistics and supply chain management
• Experience in research or applied engineering environment delivering optimisation, simulation, or decision-support systems for operational contexts
• Track record of end-to-end model delivery: problem formulation: data pipeline, algorithm design, implementation, validation, stakeholder communication

Technical Skills

• Experience or familiarity with optimisation packages such as Gurobi, CPLEX, OR-Tools, and Python PuLP for MILP formulation and solver configuration
• Experience or familiarity with simulation tools such as AnyLogic, AnyLogistix, FlexSim, Arena, AIMMS, Demo 3D or similar tools
• Proficiency in Python including pandas, numpy, scipy, scikit-learn, XGBoost, PuLP/OR-Tools, and pytest; proficiency in SQL for data queries and operational log extraction
• Experience with MS Power BI, Tableau
• Familiarity with MLflow or equivalent experiment tracking tools for ML retraining pipelines
• Proficiency in MS Office

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-%28Wave-Overtopping%29/32491-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

This position supports Work Package 1 (WP1) experimental studies of wave overtopping over Singapore-relevant coastal protection structures for local design guidance.

The successful candidate will be required to:

•     Conduct scaled physical model tests at NUS for revetments, promenades, and vertical walls
•     Measure and analyse q, Vmax, flow depth/velocity, crest pressures, and related loads; quantify uncertainty; and derive local   empirical relationships aligned with EurOtop
•     Support WP1 reports/publications and provide validation data and hydraulic inputs to other work packages.

Job Requirements

•    Possess at least a bachelor’s degree in Coastal Engineering, Ocean Engineering, Civil Engineering, Mechanical Engineering, or a closely related discipline.
•    Masters degree will be preferred. 
•    Strong background in physical modelling of coastal/free-surface flows or wave-structure interaction.
•    Experience with hydraulic laboratory experiments, instrumentation, and data analysis.
•    Proficiency in Python, MATLAB, or similar; prior wave overtopping/coastal structures experience is advantageous.
•    Has prior strong publication records and independence.
•    Excellent written and verbal 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-Fellow%2C-Computer-Science-%28School-of-Computing%29/32522-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

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

The Research Fellow will be responsible for working closely with the Principal Investigator on one or more research projects. In particular, the research fellow is going to investigate the design of novel database systems on modern hardware (e.g., GPUs and/or Non-volatile memory) and data science applications.

Only shortlisted applicants will be notified.

Qualifications

• A PhD degree in Computer Science or related field
• Experience in research and Good publication record
• Strong systems development skills

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Bayesian-Inference-&-Genomic-Epidemiology%29/32501-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 seeks a Research Fellow with deep expertise in Bayesian statistical modelling and genomic
epidemiology to contribute to methodological and applied research across several funded
programmes. Core themes include the integration of genomic, serological, and epidemiological
data into unified Bayesian frameworks; real-time inference of transmission dynamics and variant
fitness; and the development of semi-mechanistic models for arbovirus lineage surveillance across
South and South-East Asia.

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.

Key Responsibilities
• Develop and extend Bayesian semi-mechanistic renewal equation models for estimating
genotype-specific reproduction numbers and immune escape.
• Build scalable inference pipelines integrating genomic (phylogenetic/lineage) data with
epidemiological surveillance streams.
• Apply and extend deep generative modelling approaches (e.g. normalising flows,
variational inference) to handle large-scale pathogen genomic datasets.
• Contribute to real-time dashboards and toolkits for arbovirus genomic surveillance (DENV,
ZIKV) across the region.
• Publish findings in high-quality peer-reviewed journals; present at international
conferences.
• Co-supervise Research Associates and Research Assistants; contribute to grant writing
and reporting.

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 epidemiology, bioinformatics, or related field.
• Strong hands-on experience with probabilistic programming (Stan, PyMC, NumPyro,
Turing, or equivalent).
• Proficiency in Python and/or R; experience with JAX or similar autodiff frameworks is
advantageous.
• Familiarity with at least one of i) phylodynamic methods (BEAST, IQTREE, or equivalent),
ii) lineage classification frameworks, and iii) renewal equation or compartmental
transmission models.
• Track record of peer-reviewed publications.
• Strong quantitative and coding skills; ability to work in collaborative, multi-institutional research settings.

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).