Total 427 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/Senior-Research-Scientist-Remote-Sensing-Technology-&-Applications/32601-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The successful candidate will be responsible for leading research programmes in remote sensing technology and applications. He/she is expected to continuously enhance the scientific knowledge of the Centre and participate actively in remote sensing technology development and application projects. 

Experience in one or more of the following research areas will be advantageous:
* Atmospheric remote sensing : Atmospheric radiation, aerosols and clouds, particles/gases transport/dispersion modeling. 
* Aquatic remote sensing: Ocean optics, water quality, bathymetry and sea bottom characterization.
* Terrestrial remote sensing: Regional land cover/vegetation/biomass mapping, biomass burning, land use/Land cover change.
* Sensing technology and applications: Synthetic aperture radar, hyperspectral imaging, high resolution 3D modelling and precision mapping.
* Machine learning and artificial intelligence techniques for remote sensing applications.

Qualifications

• A Doctoral Degree in Science, Engineering, or in other relevant disciplines with at least 8 years of research experience in remote sensing or related fields.
• Ability to lead a team of researchers as a Principal Investigator in various research projects.

Other qualities we are looking for:
* In-depth knowledge of advanced digital data/image processing techniques and applications 
* Solid experience and skill in scientific and engineering computing 
* Ability to develop and implement data/image processing and/or machine learning algorithms 

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-%28Gen-AI%29/32616-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are looking for a Research Engineer for the OUTSMART Corp Lab led by Professor Massimo Alioto, at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).

The selected candidate is expected to:

•    circuit exploration of near-PCM and in-memory SRAM computing macros, and related models  
•    experimental validation of computing and memory macros and their support of similarity/confidence-based computation skipping, and dataflow adaptation 
•    experimental validation of test structures with dataflow adaptation in single chip, high memory-logic interspersion
•    experimental validation of chiplet interfaces and synchronization, test structures with final memory-logic aggregation, and dataflow adaptation across chiplets 
•    experimental validation of final testchip in single- and many-chiplet arrangement
•    experimental validation of final testchip in single-chiplet arrangement 

The appointment can commence immediately with a 1-year contract, with prospect of extension. Salary will be commensurate with qualifications and experience.

Qualifications

The candidate must possess:
•    Minimally a Bachelor’s degree in either Electrical Engineering or strictly related (e.g., Computer, Electronics, Communication, or Information Engineering).
•    Knowledge on circuit architectures, transistor-level design.
•    Knowledge on silicon chip design, EDA tools.
•    Ability to work independently and collaboratively in a team environment.
•    Good communication and interpersonal 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-%28Gen-AI%29/32614-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are looking for a Research Fellow for the OUTSMART Corp Lab led by Professor Massimo Alioto, at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).

The selected candidate is expected to:

•    circuit exploration of near-PCM and in-memory SRAM computing macros, and related models  
•    experimental validation of computing and memory macros and their support of similarity/confidence-based computation skipping, and dataflow adaptation 
•    experimental validation of test structures with dataflow adaptation in single chip, high memory-logic interspersion
•    experimental validation of chiplet interfaces and synchronization, test structures with final memory-logic aggregation, and dataflow adaptation across chiplets 
•    experimental validation of final testchip in single- and many-chiplet arrangement
•    experimental validation of final testchip in single-chiplet arrangement 
•    authoring high-quality research papers for leading conferences and journals and presenting findings at international conferences.
•    managing technical milestones for the project and providing technical guidance to PhD and master’s students within the group.

The appointment can commence immediately with a 1-year contract, with prospect of extension. Salary will be commensurate with qualifications and experience.

Qualifications

The candidate must possess:
•    a PhD degree in either Electrical Engineering or strictly related (e.g., Computer, Electronics, Communication, or Information Engineering).
•    Knowledge on circuit architectures, transistor-level design.
•    Knowledge on silicon chip design, EDA tools.
•    Ability to work independently and collaboratively in a team environment.
•    Good communication and interpersonal 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-%28International-Dispute-Resolution%29/29991-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The NUS Centre for International Law (CIL) is inviting applications for a one-year Research Fellow position to contribute to the development and research of the International Dispute Resolution (IDR) programme. Candidates with experience in public international law, including in international tribunals such as the International Court of Justice, are encouraged to apply. The focus topic of the IDR programme is disputes involving States and includes issues related to alternative dispute resolution, international courts and tribunals and peace and security.

The duties of the incumbent will include:

• Conducting research and writing on current issues related to the resolution of disputes involving States;
• Contributing to the development of the IDR programme's research agenda;
• Publications in top tier peer-reviewed journals;
• Development and implementation of conferences, seminars, workshops, and trainings related to international dispute resolution.

The IDR Research Fellow can look forward to working in a small team with a short reporting line and interactions with practitioners in the field. The successful candidate will also have the opportunity to collaborate with other CIL research teams and experts, and to attend conferences and workshops.

Qualifications

• A PhD in relevant area of international law or equivalent experience;
• At least 2 years of working experience;
• Proven records in conducting independent research;
• Strong analytical and writing skills - experience with publication of journal articles is desirable;
• Ability to produce academic writing as well as background papers/reports;
• Demonstrable interest in public international law and dispute resolution;
• Strong organisational and communications skills;
• Fluent language skills in English are required;
• Pro-active personality, with the ability to make suggestions and be a hands-on contributor; and
• Tech-savvy.

Application Procedures

Interested applicants are invited to apply directly via the NUS Career Portal with the following supporting documents:

• A covering letter (no more than 1 page) detailing motivations, relevant experience and why the candidate should be considered for the position;
• A detailed CV (no more than 3 pages);
• 1 sample of written work; and
• Names and contact details of 4 referees, including PhD supervisor

Please note that only shortlisted candidates will be notified and invited for an online Zoom interview.

Job Description

The National Quantum Federated Foundry (NQFF) is seeking a research engineer to join a multidisciplinary team developing essential quantum hardware and device components. The candidate will join our efforts spanning multiple quantum technology platforms ranging from trapped ions to integrated photonics and superconducting devices.

About the role

You will be embedded in a team of research scientists and engineers, contributing hands-on to the development and characterisation of quantum hardware. Based on your strengths and experience, your work will be shaped around one or more of the following focus areas:

• Device Fabrication & Engineering — Perform device fabrication and support the development and optimisation of the processes: this may include cleanroom-based nanofabrication work, electrical assembly (wirebonding, soldering, etc), and prototyping (machining, 3D printing, etc).
• Optical & Photonics Engineering — Perform optical & electrical characterization of photonics devices; construct and maintain optical measurement setups for device testing; data analysis and feedback towards improved device designs.
• Cryogenic Systems & Measurements — Set up, operate, and maintain cryogenic systems (incl. dilution refrigerators, cryostats); integrate and test quantum devices at (down to) millikelvin temperatures; develop automated testing workflows, acquire and analyse experimental data.

What we’re looking for:

• Bachelor’s degree in physics, applied physics, electrical engineering, material science & engineering, mechanical engineering, or a related discipline.
• Hands-on laboratory experience relevant to one or more of the focus areas above
• Familiarity with experimental data acquisition, analysis, and presentation
• Strong communication skills and a collaborative working style

Experience in any of the following would set you apart:

• Optical setups and laser systems
• Electrical/RF electronics and associated test equipment
• Cleanroom nanofabrication
• Mechanical design with CAD software
• Programming (especially in Python) lab equipment for testing automation

About NQFF:

The National Quantum Federated Foundry (NQFF) is a national quantum programme supporting Singapore's quantum R&D ecosystem and industry partners. Functioning as a research foundry, NQFF covers the full device development cycle — from design to fabrication and characterisation — with the goal of translating next-generation quantum devices towards real-world applications.

NQFF is hosted at A*STAR IMRE, with teams operating across A*STAR IME and the National University of Singapore (NUS).

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-Engineer-%28Gen-AI%29/32622-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are looking for a Research Engineer for the OUTSMART Corp Lab led by Professor Massimo Alioto, at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).

The selected candidate is expected to:

•    circuit exploration of near-PCM and in-memory SRAM computing macros, and related models  
•    experimental validation of computing and memory macros and their support of similarity/confidence-based computation skipping, and dataflow adaptation 
•    experimental validation of test structures with dataflow adaptation in single chip, high memory-logic interspersion
•    experimental validation of chiplet interfaces and synchronization, test structures with final memory-logic aggregation, and dataflow adaptation across chiplets 
•    experimental validation of final testchip in single- and many-chiplet arrangement
•    experimental validation of final testchip in single-chiplet arrangement 

The appointment can commence immediately with a 1-year contract, with prospect of extension. Salary will be commensurate with qualifications and experience.

Qualifications

The candidate must possess:
•    Minimally a Bachelor’s degree in either Electrical Engineering or strictly related (e.g., Computer, Electronics, Communication, or Information Engineering).
•    Knowledge on circuit architectures, transistor-level design.
•    Knowledge on silicon chip design, EDA tools.
•    Ability to work independently and collaboratively in a team environment.
•    Good communication and interpersonal 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-%28Gen-AI%29/32612-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are looking for a Research Fellow for the OUTSMART Corp Lab led by Professor Massimo Alioto, at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).

The selected candidate is expected to:

•    circuit exploration of near-PCM and in-memory SRAM computing macros, and related models  
•    experimental validation of computing and memory macros and their support of similarity/confidence-based computation skipping, and dataflow adaptation 
•    experimental validation of test structures with dataflow adaptation in single chip, high memory-logic interspersion
•    experimental validation of chiplet interfaces and synchronization, test structures with final memory-logic aggregation, and dataflow adaptation across chiplets 
•    experimental validation of final testchip in single- and many-chiplet arrangement
•    experimental validation of final testchip in single-chiplet arrangement 
•    authoring high-quality research papers for leading conferences and journals and presenting findings at international conferences.
•    managing technical milestones for the project and providing technical guidance to PhD and master’s students within the group.

The appointment can commence immediately with a 1-year contract, with prospect of extension. Salary will be commensurate with qualifications and experience.

Qualifications

The candidate must possess:
•    a PhD degree in either Electrical Engineering or strictly related (e.g., Computer, Electronics, Communication, or Information Engineering).
•    Knowledge on circuit architectures, transistor-level design.
•    Knowledge on silicon chip design, EDA tools.
•    Ability to work independently and collaboratively in a team environment.
•    Good communication and interpersonal 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-%28Gen-AI%29/32613-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are looking for a Research Fellow for the OUTSMART Corp Lab led by Professor Massimo Alioto, at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).

The selected candidate is expected to:

•    circuit exploration of near-PCM and in-memory SRAM computing macros, and related models  
•    experimental validation of computing and memory macros and their support of similarity/confidence-based computation skipping, and dataflow adaptation 
•    experimental validation of test structures with dataflow adaptation in single chip, high memory-logic interspersion
•    experimental validation of chiplet interfaces and synchronization, test structures with final memory-logic aggregation, and dataflow adaptation across chiplets 
•    experimental validation of final testchip in single- and many-chiplet arrangement
•    experimental validation of final testchip in single-chiplet arrangement 
•    authoring high-quality research papers for leading conferences and journals and presenting findings at international conferences.
•    managing technical milestones for the project and providing technical guidance to PhD and master’s students within the group.

The appointment can commence immediately with a 1-year contract, with prospect of extension. Salary will be commensurate with qualifications and experience.

Qualifications

The candidate must possess:
•    a PhD degree in either Electrical Engineering or strictly related (e.g., Computer, Electronics, Communication, or Information Engineering).
•    Knowledge on circuit architectures, transistor-level design.
•    Knowledge on silicon chip design, EDA tools.
•    Ability to work independently and collaboratively in a team environment.
•    Good communication and interpersonal 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-%28Chemical-Imaging-and-nanocatalysis%29/32625-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are looking for passionate and self-motivated postdoctoral research fellows to join our multidisciplinary team to work on the rational design of novel nanocatalysts and optical imaging for catalysis. The successful candidate will be expected to collaborate with a group of researchers from various disciplines and also assist the principal investigator in guiding junior researchers and graduate students as well as in managing project and laboratory. (https://cde.nus.edu.sg/mse/staff/ming-zhao/;  https://www.mingzhaogroup.com/)  

Qualifications

•    PhD degree in materials, chemistry, chemical engineering, physics, environmental engineering, or any other related fields.
•    Expertise in optical imaging and nanocatalysis
•    Published in reputable international journals. 
•    Responsible and able to work independently. 
•    Good written and spoken communication. 
•    Good team player across multiple disciplines. 
•    < 5 years work experience after obtaining a PhD degree

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-%28Gen-AI%29/32619-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are looking for a Research Engineer for the OUTSMART Corp Lab led by Professor Massimo Alioto, at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).

The selected candidate is expected to:

•    circuit exploration of near-PCM and in-memory SRAM computing macros, and related models  
•    experimental validation of computing and memory macros and their support of similarity/confidence-based computation skipping, and dataflow adaptation 
•    experimental validation of test structures with dataflow adaptation in single chip, high memory-logic interspersion
•    experimental validation of chiplet interfaces and synchronization, test structures with final memory-logic aggregation, and dataflow adaptation across chiplets 
•    experimental validation of final testchip in single- and many-chiplet arrangement
•    experimental validation of final testchip in single-chiplet arrangement 

The appointment can commence immediately with a 1-year contract, with prospect of extension. Salary will be commensurate with qualifications and experience.

Qualifications

The candidate must possess:
•    Minimally a Bachelor’s degree in either Electrical Engineering or strictly related (e.g., Computer, Electronics, Communication, or Information Engineering).
•    Knowledge on circuit architectures, transistor-level design.
•    Knowledge on silicon chip design, EDA tools.
•    Ability to work independently and collaboratively in a team environment.
•    Good communication and interpersonal 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-%28Living-Materials-Design-and-Development%29/26872-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

•    The Research Fellow will work closely with the Principal Investigator, Dr. LIN Yiliang, on the research project of bio-interface design between living systems and materials for healthcare and sustainable applications.
•    The Research Fellow will help to develop living materials system integrating functional hydrogels with microorganisms, perform material characterization, and investigate the real-world applications.

Job Requirements

•    A PhD degree in a relevant area, e.g., Chemical Engineering, Material Science and Engineering, Chemistry, Biomedical Engineering;
•    Good publication record;
•    Experienced bio-interface design, construction of living materials, materials characterization, and cell culture.
•    Any experience with 1) animal experiments, 2) advanced characterization techniques, and 3) soft matter mechanics and physics, is a plus
•    This position is available from Jan 2025

Job Summary

We are a project team comprising researchers from SingHealth, A*STAR, and Synapxe, developing a product to enhance the management and treatment of patients with lower respiratory tract infections (LRTIs)—a condition that accounts for nearly 489 million cases globally and is a major contributor to inappropriate antibiotic use in Singapore. 

Over 40% of prescriptions for LRTIs are unnecessary, contributing to antimicrobial resistance (AMR)—a top global health threat. Traditional stewardship programs are expert-dependent and resource-intensive, limiting scalability.

To overcome these challenges, we are building an AI-powered Large Language Model platform that uses routinely collected clinical data to help clinicians identify cases that do not require antibiotics, thereby reducing unnecessary prescriptions.

Role:

As a Research Officer, you will play a central role by integrating Large Language Models (LLMs) for intelligent processing of unstructured clinical text—such as physician notes, discharge summaries, and radiology reports. Your work will help build explainable, scalable, and real-time AI recommendations that assist clinicians at the point of care for lower respiratory tract infections.

Key Responsibilities:

• Contribute to the LLM development, focusing on enhancing unstructured data processing for clinical and biomedical applications.
• Fine-tune and train LLMs (e.g., LLaMA, Mistral, Phi, and the GPT family) using supervised and instruction-based datasets.
• Design and implement pipelines for data cleaning, preprocessing, and tokenisation of large-scale text corpora.
• Integrate retrieval-augmented generation (RAG) and knowledge graph components for domain adaptation.
• Evaluate model performance using BLEU, ROUGE, BERTScore, and factual consistency metrics.
• Develop optimised PEFT/LoRA/QLoRA fine-tuning frameworks for efficiency on GPU clusters.
• Collaborate with researchers to design experiments, interpret results, and publish findings.
• Maintain reproducible codebases, documentation, and experiment logs.

Requirements:

• Master or Bachelor in computer science, data science, artificial intelligence, computational linguistics, or related disciplines.
• Strong experience in Natural Language Processing (NLP), transformer-based models, and text generation.
• Proficiency in Python, PyTorch, Hugging Face, Transformers, and LLM fine-tuning libraries (e.g., PEFT, DeepSpeed, bitsandbytes).
• Experience with text and data processing, including annotation, tokenisation, and augmentation.
• Familiarity with vector databases (FAISS, Qdrant) and RAG pipelines.
• Understanding of GPU-based training, distributed model optimisation, and experiment tracking (e.g., MLflow, W&B).
• Strong analytical, communication, and collaborative skills.

Preferred Experience

• Research experience with open-weight LLMs or domain-specific adaptation (e.g., biomedical).
• Experience with multi-agent frameworks, prompt engineering, or LLM safety evaluation.
• Familiarity with cloud computing (AWS, Azure) or on-prem GPU clusters.

What We Offer

• Opportunity to work on cutting-edge LLM research with measurable real-world impact.
• Access to high-performance GPU infrastructure and interdisciplinary collaborations.
• Mentorship and opportunities for publication, conference presentation, and project leadership.

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.

Job Description

The Cardiovascular & Metabolic Disorders (CVMD) Programme is seeking a highly motivated Research Fellow to support and drive strategic research initiatives in the area of ageing and longevity.

The successful candidate will work closely with Professor Yibin Wang, and a multidisciplinary team of investigators, collaborators, and partners across academia, healthcare, and industry. This role is suited for a candidate with strong scientific training, project management capabilities, and the ability to coordinate complex research initiatives in a dynamic academic research environment.

This role offers broad exposure to scientific coordination, partnership development, and programme-level research management in a collaborative and intellectually stimulating environment. We welcome candidates who are scientifically grounded, proactive, and committed to advancing impactful research in ageing and longevity.

Key Responsibilities

• Provide scientific, research, and operational support to the Principal Investigator and Co-Investigators for ageing and longevity research initiatives.
• Provide logistic and technical support to a team of researchers to ensure timely achievement of project goals, milestones, and deliverables.
• Coordinate and manage complex research projects involving local and international collaborators and stakeholders.
• Oversee end-to-end project management, including grant preparation, research planning, execution, monitoring, reporting, and risk mitigation.
• Manage research-related agreements and documentation, including Research Collaboration Agreements, sub-contracting arrangements, and related records.
• Liaise with relevant institutional offices, including Contracts & Industry Engagement (CIE), Safety, Health & Emergency Response and Compliance (SHERIC), and other administrative units, to ensure compliance with contractual, regulatory, ethical, and operational requirements.
• Support intellectual property and technology disclosure processes in collaboration with researchers and the Office of Innovation and Entrepreneurship (OIE).
• Support the planning and execution of programme-related meetings, workshops, seminars, partnership engagements, and outreach activities.
• Contribute to strategic planning, programme development, and reporting to strengthen Duke-NUS ageing and longevity research portfolio.

Job Requirements

• PhD in a relevant scientific discipline and/or a postgraduate Medical Degree, with at least 3 years of relevant experience in an academic, research institute, healthcare, or institute of higher learning environment.
• Strong experience in research coordination, programme management, or project management, preferably in a multidisciplinary research setting.
• Demonstrated ability to manage multiple stakeholders, timelines, and deliverables effectively.
• Experience in translational research, strategic research development, or industry-linked projects will be an advantage.
• Familiarity with research contracts, compliance processes, and/or intellectual property management would be advantageous.
• Strong organisational, analytical, and problem-solving skills, with the ability to work under tight timelines.
• Good financial awareness and experience in budget planning or grant-related processes will be an advantage.
• Excellent written and verbal communication skills, with strong interpersonal skills.
• Experience working with international collaborators or external partners is desirable.
• Self-motivated, resourceful, detail-oriented, and able to work both independently and collaboratively.

We regret that only shortlisted candidates will be notified.

Responsibilities:

• Lead and drive applied R&D projects in the areas of Battery Management Systems (BMS), Energy Storage Systems (ESS), and green power technologies.
• Conduct system-level research on battery safety, performance, reliability, and external monitoring for lithium-ion, sodium-ion, and other emerging battery systems, with a focus on practical engineering applications rather than materials development.
• Develop control, monitoring, diagnostic, and optimisation solutions for battery systems, ESS, and hybrid energy platforms. Design and implement energy management strategies for integrated clean energy systems involving batteries, solar PV, hydrogen/fuel cells, and other hybrid power configurations. Support the development of ESS solutions for grid stability, resilience, and efficient energy utilisation in distributed energy and microgrid applications.
• Advance the use of digital twin and AI-enabled approaches for battery systems, ESS, solar energy, hydrogen, and other green energy platforms to improve monitoring, control, optimisation, and predictive maintenance.
• Development of innovative prototypes, proof-of-concept systems, and demonstration platforms for industry-relevant applications.
• Identify, develop, and secure research funding opportunities through grants, industry-sponsored projects, and strategic collaborations. Prepare and manage project proposals, technical reports, research publications, presentations, and related documentation. Build and maintain partnerships with industry, government agencies, and research institutions to support technology translation, validation, and deployment.
• Provide training and mentorship for industry professionals and Temasek Polytechnic students through project supervision, applied learning activities, workshops, and short courses.
• Support the Centre’s strategic growth in the areas of battery management, energy storage, and green power, aligned with emerging industry and national priorities.

Pre-requisites:

• Qualifications in Electrical/Electronic Engineering, Computer Engineering, Automation, Power Engineering, Computer Science, or a related field. Postgraduate qualifications are preferred.
• Relevant R&D or industry experience of 2–8 years in Battery Management Systems (BMS), Energy Storage Systems (ESS), battery systems, or green power technologies.
• Good knowledge of battery safety, performance, reliability, monitoring, and system integration. Familiarity with integrated energy systems involving batteries, ESS, solar PV, hydrogen/fuel cells, or hybrid power platforms.
• Experience in control, diagnostics, optimisation, or energy management for electrical or energy systems. Exposure to digital twin, AI-enabled methods, or intelligent system applications in battery, ESS, or green energy areas will be an advantage.
• Practical experience in hardware and software development, embedded systems, instrumentation, prototyping, system integration, and testing.
• Experience in project proposal writing, research planning, technical reporting, and R&D project execution. Experience in industry collaboration and applied research will be an advantage.
• Strong analytical, problem-solving, communication, and teamwork skills, with the ability to work independently in a multidisciplinary environment.
• Passion for advancing battery, energy storage, and green power technologies with practical industry impact.

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-%28VIOLIO-&-State-Estimation%29/32580-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

A Research Fellow position is open in a research lab 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 the project “Meta-Learning of Robust State Estimation for Agile Mobile Robots.” The position focuses on advancing state estimation and odometry for robotic systems, with particular emphasis on LiDAR-Inertial Odometry (LIO), Visual-Inertial Odometry (VIO), and multi-sensor fusion for UAVs and other agile platforms.

The Research Fellow will develop high-performance, robust estimation algorithms that operate reliably in challenging environments (e.g., low texture, illumination variation, dynamic scenes, or sensor degradation). The research will integrate model-based estimation methods (e.g., filtering, factor graph optimization, moving horizon estimation) with learning-enhanced components, including meta-learning approaches for adaptive and generalizable estimation.

The candidate will be responsible for both theoretical development and system-level implementation, including real-time deployment on robotic platforms. The developed algorithms will be validated through simulation and real-world experiments, particularly on UAV systems.

In addition, the Research Fellow is expected to contribute to mentoring junior PhD students and supporting research activities within the project.

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 Ph.D. degree from a reputable university, with expertise in robotic state estimation, SLAM, or perception for autonomous systems.

A successful candidate should have a strong mathematical background (e.g., linear algebra, optimization, probability, stochastic processes), and a strong publication record in top-tier venues. 

Qualifications

•    Possess a Ph.D. degree in Electrical Engineering or related disciplines (e.g., Computer Science, Robotics, Mechanical Engineering, Aerospace, Mathematics).
•    Have substantial research experience in robotic state estimation, SLAM, or odometry systems.
•    Strong expertise in LiDAR-Inertial Odometry (LIO), Visual-Inertial Odometry (VIO), or multi-sensor fusion.
•    Solid understanding of estimation and optimization frameworks, including EKF/UKF, factor graph optimization, bundle adjustment, or moving horizon estimation (MHE).
•    Experience with real-time perception systems and deployment on robotic platforms.
•    Proficient in C++ or Python; experience with ROS and robotic middleware.
•    Familiar with UAV systems (e.g., PX4), and simulation environments such as Gazebo or AirSim.
•    Experience with sensor calibration, time synchronization, and system integration is highly desirable.
•    Strong publication record in leading journals and conferences in robotics, control, or machine learning.
•    Excellent communication skills and ability to independently publish and present research outcomes.
•    Demonstrated ability to supervise students or contribute to research leadership is preferred.
•    Experience in world-class research environments is highly valued.
•    Open to Fixed Term Contract