Total 590 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-Associate-%28Biostatistics-and-Modelling%29/33200-en_GB/?st=141BEF5F2248FFEB18DC476F6C0C960C34CB32A1

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 (1 year in the first instance)

A research associate position is available in the Saw Swee Hock School of Public Health to support the Principal Investigator, Assistant Professor Hannah Clapham, in research projects in the areas of Biostatistics and Modelling. This post will work on a project studying dengue disease dynamics and burden using mathematical and statistical models.

The research associate will work on statistical and mathematical modelling projects. Major duties and responsibility of the post includes:
- analysing data using statistical and mathematical modelling techniques,
- writing reports, presentations, and publication of results and findings in peer-reviewed journal,
- supervising junior staff as required

Candidate must:
- have two years of research experience in mathematical or statistical modelling applied to the field of epidemiology
- be an independent worker who is well- organized and has an eye for detail.
- possess excellent written and verbal communication skills,
- possess the ability to work effectively with colleagues to achieve team goals,
- have good proficiency in Statistical software (R),
- have experience in the application of quantitative methods to epidemiology and public health questions,

It would be desirable for the candidate to:
- have relevant research experience as part of a degree or post-degree in academia or in industry.
- have research experience beyond that listed above
- have experience of literature reviews and/or analysing epidemiological data

Recruitment is open immediately, and will continue until the position is filled. Applicants should send a brief statement of interest, CV, three named references, and other supporting documents during the application.

For further enquiries, please contact Dr Hannah Clapham at hannah.clapham@nus.edu.sg

We regret that only shortlisted candidates will be notified.

Qualifications

Possess a masters level degree in Computer Science, Mathematics, Statistics, Engineering, Physics

Job Responsibilities:

• Develop and sustain Dry etch processes in R&D and Small volume manufacturing environment
• Responsible for performing professional process engineering research, from the concept to the final process development for a wide variety of materials (Metals, Silicon, Dielectrics, SiC and other speciality materials)
• May conceive and plan projects involving the definition and selection of new materials, concepts and approaches in the processing or developing of new processes.
• Compiles and evaluates test data to determine appropriate limits and variables for process specifications.
• Championing engineering experiments for process characterization to drive quality and yield improvementSet up and collect the experimental data and generate reports for internal and customer distribution.
• Design and complete DOE (Design of Experiments) evaluations to characterize process window for new requirements
• Work closely with senior staff and process integrators to understand technology roadmaps, process capability requirements and business issues/ challenges.
• Act as a resource for colleagues with less experience; lead small projects with manageable risksAct as subject matter expert for both internal and external stakeholders.

Requirements:

• PhD in Materials Science, Metallurgy, Electrical, Electronics, Chemical Engineering, Chemistry or Physics; or relevant field science and engineering fields.
• PhD graduates with plasma or semiconductor process exposure are added advantages.
• Prior experience in dry etch/Wet etch processes is preferredKnowledge of plasma fundamentals is an added advantage
• Hands-on experience in designing and executing experiments (DOE), statistical and cause analysis, and problem-solving methods
• Possess good interpersonal and communication skills

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-%28Fluid-mechanics%29/33185-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

•    Conduct computational fluid dynamics (CFD) simulations 
•    Conduct experiments in wind tunnels and water channels
•    Analyze experimental and simulation data and summarize key findings and observations
•    Collaborate with other team members to design experiments, develop simulation methodologies, data collection and analysis
•    Assist in the preparation of research proposals and technical reports
•    Lead and contribute to peer-reviewed publications, conference presentations, and internal research reporting
•    Maintain organised research workflows (version control, reproducible experiments, 3D model management, documentation).
•    Support broader project goals as needed (e.g., dataset curation, method benchmarking, cross-validation of simulations with actual measurements)

Job Requirements

•    PhD in Mechanical/Civil/Environmental Engineering or equivalent
•    Proficiency in computational fluid dynamics (CFD) simulations software
•    Proficiency in wind tunnel and water channel experiments
•    Strong passion in research and can conduct research independently
•    Fluent in English and able to present research to both researchers and the general public 
•    Strong publication record

About TUMCREATE

TUMCREATE is a multidisciplinary research platform of the Technical University of Munich (TUM) at the Singapore Campus for Research Excellence and Technological Enterprise (CREATE). We are partnering with universities, public agencies, and industry to advance future technologies.

The HEARTwise project is a public-private research initiative funded by Singapore's National Research Foundation, bringing together clinical cardiologists (CADENCE / NUHS, NHCS), engineers from TUM and TUMCREATE, and MedTech partners. The project develops a multimodal platform for non-invasive, early decompensation detection in ambulant HF patients – combining wearable mobility sensing, heart and lung sound recognition, and integration with additional digital biomarker sources.

As a member of the HEARTwise team, you will collaborate within an interdisciplinary consortium comprising leading experts in cardiology, telemedicine, biomedical engineering, acoustics, data privacy, and industry.

Please visit www.tum-create.edu.sg for more information about TUMCREATE.

Background & Scientific Context

Heart failure (HF) affects 2.5% of Singapore's population and is the leading cardiac cause of hospital admission – presenting a decade earlier and more aggressively than in Europe or North America. The 30% rehospitalization rate within 90 days of discharge is both a major clinical burden and a window of opportunity for early, data-driven intervention.

Job Summary

We are seeking a highly motivated and skilled researcher with proven expertise in machine learning for audio analysis. Within HEARTwise at TUMCREATE, you will lead the development of artificial intelligence algorithms for audio classification of heart and lung sounds. Through multimodal integration with data from mobility sensing and other biomarkers, you will create a reliable tool for early decompensation detection in ambulant HF patients. You will be working in a team developing a tool for audio data collection in the clinic, running a clinical study for data collection, working with clinicians to create an annotated database, and validating your classification prototype in a pilot clinical diagnostic study.

This is a fixed-term contract until March 2029 when applicable.

Key Responsibilities

• Develop prototype algorithms for audio classification of heart and lung sounds.
• Contribute to clinical data collection, database building, multimodal data analysis,clinical prototype app development.
• Verify the technology against requirements and validate in a pilot clinical study.
• Collaborate with experts in cardiology, telemedicine, biomedical engineering, acoustics, and data privacy
• Write scientific manuscripts, contribute to project reports, and present findings at international conferences and stakeholder meetings.

Key Competencies

• At least 1 year of proven expertise in deep learning signal analysis,preferably with audio data.
• Excellent written and verbal communication skills in English, with the ability to communicate complex analytical results to multidisciplinary teams.
• Demonstrated ability to work independently and collaboratively in a fast-paced, international research environment.

Qualification Requirements

• We are seeking a researcher with a PhD degree in electrical engineering,physics, data science, computer science, or similar, and a proven track record in machine learning and (audio) signal processing. Fresh graduates and PhD candidates will also be considered.
• Proficiency in Python/Matlab and anaconda (or similar).
• Experience in C/C++ and database interfacing and in user or clinical studies is desirable.
• Ideally, the candidate has an interdisciplinary education including acoustics that facilitates collaboration with biomedical engineers.

What we offer

• A collaborative and inclusive world-class research environment.
• Opportunities for professional development.
• Engagement with a leading international team addressing interdisciplinary challenges in heart failure management.

Applications

Please submit the following compulsory documents to hr@tum-create.edu.sg:

• Cover letter
• CV
• University transcripts

Only shortlisted candidates will be contacted.

We look forward to your application!

About TUMCREATE

TUMCREATE is a multidisciplinary research platform of the Technical University of Munich (TUM) at the Singapore Campus for Research Excellence and Technological Enterprise (CREATE). We are partnering with universities, public agencies, and industry to advance future technologies.

The HEARTwise project is a public-private research initiative funded by Singapore's National Research Foundation, bringing together clinical cardiologists (CADENCE / NUHS, NHCS),engineers from TUM and TUMCREATE, and MedTech partners. The project develops a multimodal platform for non-invasive, early decompensation detection inambulant HF patients – combining wearable mobility sensing, heart and lung sound recognition, and integration with additional digital biomarker sources.

As a member of the HEARTwise team, you will collaborate within an interdisciplinary consortium comprising leading experts in cardiology, telemedicine, biomedical engineering, acoustics, data privacy, and industry.

Please visit www.tum-create.edu.sg for more information about TUMCREATE.

Background & Scientific Context

Heart failure (HF) affects 2.5% of Singapore's population and is the leading cardiac cause of hospital admission – presenting a decade earlier and more aggressively than in Europe or North America. The 30% rehospitalization rate within 90 days of discharge is both a major clinical burden and a window of opportunity for early, data-driven intervention.

Job Summary

We are seeking a highly motivated and skilled researcher with proven expertise in signal processing, in user or patient research studies, and in creating software for participant testing. You will collaborate with clinicians and be responsible for audio data collection of heart and lung sounds in the clinic, for creating an annotated database, and for validating sound classification prototypes in a pilot clinical diagnostic study. You will work on prototype algorithms for classification of heart and lung sounds and develop approaches for integrating multimodal data from mobility sensing and other biomarkers to create a reliable tool for early decompensation detection in ambulant HF patients.

This is a fixed-term contract until March 2029 when applicable.

Key Responsibilities

• Work on classification algorithms of heart and lung sounds, on multimodal data analysis and fusion, and on verifying the technology against requirements.
• Work with clinicians on data collection from heart failure patients and build a database under consideration of data protection and ethical requirements
• Develop a tool for audio data collection in the clinic, advance it into a clinical audio classification prototype and validate it in a pilot clinical study.
• Collaborate with experts in cardiology, telemedicine, biomedical engineering, acoustics, and data privacy
• Write scientific manuscripts, contribute to project reports, and present findings at international conferences and stakeholder meetings.

Key Competencies

• At least 1 year of proven expertise in signal processing, user or patient studies, and in creating software for participant testing.
• Excellent written and verbal communication skills in English, with the ability to communicate complex analytical results to multidisciplinary teams.
• Demonstrated ability to work independently and collaboratively in a fast-paced, international research environment.

Qualification Requirements

• We are seeking a researcher with a PhD degree in hearing research, electrical engineering, biomedical engineering, human factors engineering, (medical) physics, computer science or similar and a proven track record in (audio) signal processing and in developing and conducting research studies with users or patients. Fresh graduates, PhD candidates and Engineers in similar fields will also be considered.
• Proficiency in C/C++,Matlab/Python and anaconda (or similar).
• Experience in machine learning and database interfacing is highly desirable.
• Ideally, the candidate has an interdisciplinary education including acoustics that facilitates collaboration with biomedical engineers.

What we offer

• A collaborative and inclusive world-class research environment.
• Opportunities for professional development.
• Engagement with a leading international team addressing interdisciplinary challenges in heart failure management.

Applications

Please submit the following compulsory documents to hr@tum-create.edu.sg:

• Cover letter
• CV
• University transcripts

Only shortlisted candidates will be contacted.

We look forward to your application!

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Computer-Science%29/33203-en_GB/?st=148CE054359BE2C7B80B2B9D9F4D62543197147D

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 conduct research in areas of efficient AI, multimodal understanding, vision and robotics.

Only shortlisted applicants will be notified.

Job Requirements

• Ph.D. in Computer Science or a closely related field
• Excellent research skills, including data analysis, interpretation, and scientific writing
• Good publication record
• Strong communication and collaboration skills
• Ability to work independently and manage multiple tasks effectively

Nurse | Clinical Research Unit

• Office Location: Buona Vista, Singapore
• Working Hours: Flexible
• Monthly Salary: Hourly Rate
• Employment Type: Full time, Permanent Contract

Company Overview

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

Responsibility

• Clinical Care Excellence – Deliver professional and high‑quality care in the management of clinical trial subjects/volunteers within the Clinical Research Unit (CRU).

• Confidentiality & Privacy – Safeguard subject/volunteer privacy and maintain strict confidentiality of all privileged information.

• Data Management – Collect, verify, and ensure proper storage of trial data in compliance with protocols.

• Biomedical Equipment Operation – Operate biomedical equipment proficiently to support clinical trial activities.

• Safety Compliance – Apply standard safety measures to protect self and others from biohazard materials, including blood‑borne pathogens.

• Trial Execution Support – Follow instructions from the Study Nurse‑in‑Charge to ensure smooth execution of clinical trial activities.

Requirement

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

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

Recruit Lync Pte Ltd | EA License Number: 22C1000

Chen Hoe Nam | EA Personnel License: R25158678

Research Technologist

• Office Location: Buona Vista, Singapore
• Working Hours: Shift work
• Monthly Salary: Hourly Rate
• Employment Type: Full time, Permanent Contract

Company Overview

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

Responsibility

• Sample Management – Assist in laboratory kit preparation, ensure proper processing, labeling, storage, and shipment of biological samples in compliance with protocol, GCP, GLP, and SOPs.

• Data & Record Accuracy – Perform data entry, verification, and maintain detailed records to reflect current workflow processes.

• Quality Assurance – Conduct quality checks on shipping documents, monitor temperature‑controlled products, and ensure compliance with sponsor requirements.

• Laboratory Equipment Maintenance – Perform routine checks, maintain inventory, and adhere to quality control processes for laboratory equipment operations.

• Calibration & Documentation – Support calibration, qualification, and validation of biomedical systems; maintain proper documentation for traceability and preventive maintenance.

• Team Collaboration – Work closely with Research Technologists to ensure equipment readiness and operational compliance across laboratory processes.

Requirement

• Minimum Diploma in Health Science
• Good interpersonal and communication skills, with the ability to coordinate effectively.
• Candidate who can start immediately or within short notice will be preferred

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

Recruit Lync Pte Ltd | EA License Number: 22C1000

Chen Hoe Nam | EA Personnel License: R25158678

REPORTS TO: Middle & High School Principal

JOB GOAL: A High School Science teacher at ICS must have a strong understanding of the Next Generation Science Standards (NGSS) and have experience closing the achievement gap. They must develop engaging and innovative lessons that allow our students to grow academically, socially and emotionally. The teacher should be confident in incorporating technology (including emerging technologies such as GenAI) and hands-on learning experiences into the classroom with enthusiasm and also believe in collaboration with other colleagues, promoting understanding and communication in a diverse learning and cultural environment.

PERFORMANCE RESPONSIBILITIES:

• Plan, prepare, and execute appropriate lessons, utilizing appropriate resource materials and activities.
• Follow the prescribed scope and sequence of curriculum and assessment as scheduled.
• Employ a variety of instructional aides, methods, and materials that will promote best practices in order to reach the whole child as stated in the ICS mission statement.
• Assess student learning against the appropriate standards on a regular basis and provide progress reports as required.
• Identify the needs of students through diagnostic procedures and align instructional objectives to these needs.
• Effect student learning through mastery of the subject material by utilizing valid teaching techniques to achieve curriculum goals within the framework of the school’s philosophy.
• Eager to explore and learn about emerging technologies, such as Generative AI, with a commitment to integrating them effectively into the classroom to foster critical thinking and guide students in developing ethical and responsible use.
• Ensure Biblical Worldwide Integration (BWI) is mapped throughout the curriculum.
• Complete lesson/unit plans, Atlas, ESO documentation, and PLC expectations within specified time frames.
• Maintain student records as required by the school.
• Communicate with parents, students, and other professional staff regarding student progress (behavioral and academic).
• Follow school policies, procedures, rules, regulations, and guidelines and the provisions of the contract.
• Maintain proper discipline in the classroom and on the school premises utilizing teacher created discipline plans in conjunction with a school-wide discipline plan.
• Inform the administration if/when unable to fulfill any duty assigned. Prepare adequate information and materials for a substitute teacher.
• Plan and lead a student Chapel when called upon.
• Supervise extracurricular activities, organizations, and outings as assigned.
• Complete the Christian Philosophy of Education in-service program within the first three years of teaching at ICS.
• Attend and participate in devotions, teachers’ meetings, evening programs (if involving his or her students or as requested by the administration), and other meetings as assigned.
• Carry out supervisory duty as assigned (before school, break, lunch, after school).
• Maintain a classroom in a clean and educationally stimulating environment.
• Maintain regular and accurate attendance and grade reports that provide comprehensive information for each student’s learning progress.
• Keep students, parents, and the administration informed of students’ progress or deficiencies, and provide sufficient and timely notice to parents when students fail to meet learning standards.
• Submit all appropriate reports to the administration, guidance office, and business office as required by school regulations or as requested.
• Work with the administration in implementing all policies, procedures, and directives governing the operation of the school.
• Complete professional development programs as required by the administration and/or ICS Board.
• Maintain teaching credentials as required through sponsoring agencies (state/provincial education department, ACSI, etc.). Acquire and maintain teaching credentials as required by the laws of Singapore, NICS, and/or ICS.
• Demonstrate the character qualities of enthusiasm, courtesy, flexibility, integrity, kindness, self-control, perseverance, and punctuality.
• Exemplify strong interpersonal and communication skills.
• Meet everyday stress with emotional stability, objectivity, and optimism.
• Develop and maintain rapport with students, parents, and staff by treating others with friendliness, open-mindedness, dignity, and consideration.
• Respectfully submit to and demonstrate loyalty to constituted authority.
• Maintain a personal appearance that models cleanliness, modesty, good taste, and is in agreement with school policy.

QUALIFICATIONS:

• Bachelor’s Degree
• Teaching credential from a US state, Canadian province or from ACSI (exceptions will be approved by the Academic Board)
• Expertise in working with students and teaching Advanced Placement (AP) courses
• Knowledge of specific subject(s)

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-%28Health-District-Evaluation%29/33186-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Health District @ Queenstown (HD@QT) is a multi-stakeholder initiative led by the National University of Singapore (NUS), the National University Healthy System (NUHS), and the Housing &

Development Board (HDB), in partnership with public, private and community stakeholders.

It provides a platform to co-develop and test innovative programmes that support active and

purposeful ageing, foster intergenerational participation, strengthen community resilience, and

advance progress toward the longevity dividend, starting in Queenstown. Home to about 101,480 residents, Queenstown is Singapore’s oldest housing estate, with 76.2% of residents living in public housing. It is also a super-aged community, with 22.2% of residents aged 65 and above. In 2021, Queenstown was designated Singapore’s first Health District, serving as a testbed for integrated solutions to support ageing well. Insights and successes from Queenstown will inform future programmes across Singapore.

Mission and Goals: At Health District @ Queenstown, we empower residents to stay healthy, engaged and connected throughout their lives, within a supportive and inclusive community. By co-creating and co-developing effective, scalable, and sustainable programs, we aim to:

1. Increase healthy longevity

2. Enable purposeful longevity

3. Promote intergenerational bonding

4. Empower ageing in place

Focus Areas

Since its launch in October 2021, Health District @ Queenstown has focused on six key areas:

1. Preventive Health and Care Delivery

2. Purposeful Longevity

3. Community & Urban Living

4. Technology & Innovation

5. Evaluation

6. Communications & Engagement

The Evaluation pillar, led by National University of Singapore and National University Health System, aims to understand how Queenstown residents are doing today, and how things may change over time. We collect insights from residents through a Baseline Study and track the progress of Health District @ Queenstown towards its goals through the development of a Health District Evaluation Framework. In consultation with our International Advisory Panel, we assess the effectiveness and scalability of initiatives for Queenstown residents across five key areas:

• Well-being
• Productivity and engagement
• Security
• Equity
• Cohesion

We take a well-rounded approach that includes engaging residents and partners, alongside data analysis, to help us understand the potential for scaling up successful initiatives. 

Job Responsibilities*

You will be responsible for the following:

• Conduct qualitative data management, including coding and analysis of focus group discussions (FGDs) and in-depth interviews, and perform in-depth thematic analysis to identify key themes and sub-themes and translate findings into research outputs
• Lead and prepare qualitative research manuscripts for publication in peer-reviewed journals
• Plan and support the co-design and implementation of community-based interventions, including engagement with specific population groups (e.g., younger Malay residents)
• Support research protocol development and study design, ensuring alignment with ethical and regulatory requirements
• Contribute to grant development and submission, including one grant resubmission (SSRTG) and one new competitive grant application (e.g., NMRC or equivalent funding schemes)
• Contribute to dissemination of research findings through reports, presentations, and academic publications

Qualifications

• Hold a Master’s degree in Social Sciences, Public Health, Psychology, Sociology, or a related discipline with training in qualitative research methods
• Experience in qualitative research, including conducting interviews/FGDs, coding, and thematic analysis
• Proficiency in qualitative data analysis approaches and/or software (e.g. NVivo) is preferred
• Demonstrated experience in academic writing, preferably including peer-reviewed manuscript preparation or submission
• Experience in research administration tasks such as ethics applications, study documentation, and/or grant proposal development is preferred
• Strong written and spoken English communication skills
• Proficiency in Microsoft Office (Word, Excel, PowerPoint)
• Experience working in healthcare or community-based research settings is an advantage
• Ability to communicate in a second local language (e.g. Mandarin, Malay, Tamil) is an advantage, as the role may require handling transcripts and conducting analysis involving participants who communicate in their mother tongue
• Open to local residents (Singapore citizen or Permanent Resident) only

The initial appointment is for 1-year. This is a full-time position based in Singapore.

Applicants should send the following by email to the NUS Career Portal:

1. 1. A two-page Curriculum Vitae (only including relevant information), previous experience and containing details of two named referees
   2. A sample of published work and their roles in the projects (if applicable)
   3. Two letters of reference

Interviews will be face to face for local candidates.  Please note that only shortlisted candidates will be contacted.

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Hydrodynamics-of-Coastal-Structures%29/33192-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

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

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

Job Requirements

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

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Offshore-Geotechnical-Engineering%29/33194-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Research Fellow (RF) will be responsible for leading and managing research activities related to the project titled Offshore Geotechnical Engineering. 

Key duties include conducting offshore soil- structure cyclic loading for Coastal Structures and supervising research assistants and ensuring compliance with safety and ethical standards and contributing to the preparation of progress reports and grant documentation.

Qualifications

•    Possess at least a PhD degree in relevant fields include Civil Engineering, Ocean Engineering, Fluid Mechanics, Computer Science, or related disciplines. Applied Mathematics, Data Science, Electrical and Electronics Engineering, Earth Sciences, Remote Sensing, and Artificial Intelligence are also well-suited. (More details on PhD requirements can be found at: https://nusgs.nus.edu.sg/scholarships/nus-research-scholarship/)
•    Strong written and spoken communications. 
•    Demonstrated strong research interest, skills, and experience.
•    Proficiency in programming languages (e.g., Python, MATLAB) and experience with data analysis tools.
•    Ability to work both independently and collaboratively within a multidisciplinary team.
•    Open to fixed-term contract. 

Interested applicants are invited to apply directly at the US 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-%28Coastal-and-Marine-Cluster%2C-EMID%29/33199-en_GB/

We regret that only shortlisted candidates will be notified.

Duties and Responsibilities

• Assist in marine environmental research
• Regular field trips onboard research vessels that may extend outside conventional office hours
• Coordination of field trips, logistics and pre-field preparation
• Post-field processing of samples, including identification of specimens and image processing
• Purchasing of consumables and equipment
• General administrative duties
• General maintenance of laboratories and equipment
• Curation of reference collection
• Data management, analysis, interpretation and reporting

Qualifications and Requirements

• Bachelor’s degree or equivalent with a major in Marine Biology
• Strong background in coral ecology and/or biostatistics
• SCUBA Divers with a minimum of Rescue diver certification and/or 100 logged dives will be given priority
• Experience with LIT survey techniques
• Troubleshooting and analytical skills
• Honest, highly motivated, resourcefulness, independence and a desire to learn
• Proficiency in MS Office applications, LaTeX and R
• Excellent written and verbal communication skills in English
• A background in ecological or mathematical modelling is a bonus

Application Procedure

Interested candidates are invited to email their detailed resume and cover letter to the NUS Career Portal.

Candidates who do not hear from us within 8 weeks after the closing date of the advertisement may assume that the post has been filled.

Only shortlisted candidates will be notified

Closing Date: 15 July 2026

Additional Information

Salary will commensurate with qualifications and experience. The appointment will be for a period of one year and extendable depending upon the candidate’s performance. 

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-%28Operations-Research-&-Analytics%29/33202-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are seeking a Research Assistant to support research in machine learning and operations research, with a focus on multi-agent reinforcement learning and stochastic inventory control.

Responsibilities

• Conduct research on multi-agent reinforcement learning.
• Complete both the queueing version and the general version of the research project.
• Support the completion and submission of a paper on stochastic inventory control with latent queues.
• Perform mathematical analysis, programming, simulation, and model development as needed.
• Collaborate with team members on research design, implementation, and writing.
• Contribute to preparing research outputs, including reports, presentations, and manuscripts.

Qualifications

• A completed bachelor’s degree in management science, business, computer science, industrial engineering, or a related field.
• Evidence of the ability to conduct high-quality research.
• Strong background in mathematics and programming.
• Strong problem-solving skills.
• Ability to work effectively in a collaborative team environment.
• Excellent communication 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-%28Diagnostic-Radiology%29/33182-en_GB/?st=E46E8C661AA4B677806A9C46B535F8BA84606614

We regret that only shortlisted candidates will be notified.

Job Description

The National University of Singapore invites applications for multiple Research Fellow positions in Yong Loo Lin School of Medicine, Department of Diagnostic Radiology. Appointments will be made on a 1-year contract basis in the first instance, with the possibility of extension.

Purpose of the post

The PI lab aims to develop nucleic acids nanobiotechnology for RNA therapy and gene editing. The Research Fellow will be responsible to, and work closely with, the Principal Investigator and the team members to undertake independent and/or collaborative research and to lead on aspects of research strategy within the lab.

The Research Fellow will be able to:

(1) Undertake advanced research in the relevant discipline area using, or developing, the appropriate methods and/or techniques and help mentor graduate students assigned to the project;

(2) Lead and promote activities designed to develop collaborative research with research colleagues and support staff internally and to actively develop appropriate external contacts and networks relevant future collaboration and funding opportunities; Maintain the highest standard of professional conduct and record keeping in accordance with policies and procedures;

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

Qualifications

• Applicants should possess a Ph.D. (preferably in chemical engineering, molecule cloning, cancer immunology) with previous experience in designing research projects.
• A detailed knowledge of molecular imaging probes and/or nanomedicine is mandatory.
• Ability to design and perform scientific work independently and collaboratively is a must, as is the ability to thrive in a fast-paced environment.
• Experience in any of the following areas will be considered: chemistry and radiochemistry, biomaterials, nanomedicine, immunology, molecular imaging, theranostics and translational research.
• Motivation and the drive to work hard and learn new skills are most important.

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

Only shortlisted candidates will be notified.