Total 614 Science / R&D / Research job vacancies in PASIR GUDANG

Senior Research Nurse

• Office Location: Buona Vista, Singapore
• Working Hours: Morning/Noon Shift (45 hours per week)
• Monthly Salary: Hourly Rate + Completion Bonus
• Employment Type: Full time, Permanent Contract

Company Overview

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

Responsibility

• Clinical Care & Excellence – Deliver professional care and management of clinical trial participants, ensuring privacy and confidentiality at all times.
• Data & Equipment Handling – Collect, verify, and store trial data accurately; operate biomedical equipment proficiently within the CRU.
• Safety & Emergency Preparedness – Apply biohazard safety precautions and participate actively in Code‑blue drills, leading during real emergencies.
• Screening & Trial Execution – Perform general screening activities and protocol‑related tasks under the guidance of the Study Nurse‑in‑Charge.
• Collaboration & Coordination – Work closely with pharmacists, technologists, and support staff to ensure smooth execution of trial activities and auxiliary services.
• Compliance & Documentation – Adhere to SOPs, GCP, and regulatory requirements; maintain accurate records and demonstrate commitment to training and policy compliance.

Requirement

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

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

Recruit Lync Pte Ltd | EA License Number: 22C1000

Chen Hoe Nam | EA Personnel License: R25158678

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Infectious-Disease-Modelling%29/29829-en_GB/?st=10D7DF6900EEA4DFBE1D5F37204E9A8E4AB59151

We regret that only shortlisted candidates will be notified.

Job Description

Qualifications

● A Ph.D. in a relevant field such as computer science, statistics, epidemiology, computational biology, bioinformatics, biostatistics, machine learning, or a related discipline.
● Strong background in at least one of infectious disease modelling, phylogenetics, or phylodynamics (background in computational statistics or machine learning is optional but highly relevant)
● Proficiency in programming languages (R, Python, C++, Java or Julia).
● Experience with mathematical and statistical methods applied to real-world, public health, and global health problems.
● Excellent written and verbal communication skills, including presenting complex concepts to diverse audiences.
● Demonstrated ability to work effectively in a multidisciplinary team and independently.
● Track record of publications in peer-reviewed journals

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Hydrodynamics-of-Coastal-Structures%29/33191-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

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

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

Job Requirements

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

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

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

We regret that only shortlisted candidates will be notified.

Job Description

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

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

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

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

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

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

Qualifications

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

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

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

We are committed to open science, equitable partnerships, and scientific rigour. Candidates who share these values are strongly encouraged to apply.

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Senior-Manager-%28IT-Project-and-Product-Management%29-Faculty-and-Research-Systems/32747-en_GB/

We regret that only shortlisted candidates will be notified.

About NUS IT

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

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

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

https://nusit.nus.edu.sg/ 

Job Description

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

Duties and Responsibilities

Product Development & Lifecycle Management

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

AI Solution Delivery

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

Project Delivery

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

Strategic Partnership & Faculty Engagement

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

Operations & Continuous Improvement

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

Qualifications

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

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

The Genome Institute of Singapore (GIS) is Singapore"s flagship institute for the genomic sciences. The Agency for Science, Technology, and Research (A*STAR) is the parent funding body for the GIS and has a long-term commitment to advance science and develop innovative technology to further economic growth and improve lives. As one of the world"s premier genomic centres, the GIS integrates genetics, genomics, high-throughput biology, and data science to gain fundamental, translational, and clinical insights into human disease and health (https://www.a-star.edu.sg/gis/).

We welcome applications at all levels, including candidates seeking their first independent Principal Investigator position (equivalent to first-time Assistant Professor at academic institutions) and execptionally qualified established leaders in their fields (at the level of Associate/Full Professor) to develop their independent research programmes in the following domains:

• Develop novel high throughput technologies for unveiling new insights into the biology of DNA or RNA. Candidates with an established track record in sequencing methodology development, genomics, functional genomics (studied using saturation mutagenesis), and molecular engineering are highly welcome.
• Develop novel technologies in RNA therapeutics (including either using RNA as medicine or targeting RNA in diseases). Candidates with an established track record in targeting RNA or engineering RNA for protein production, decay, and localization in health and disease systems are strongly encouraged to apply.
• AI to leverage state-of-the-art artificial intelligence to design and implement or use generative models targeting RNA, DNA, and cellular systems,
• Computational biology, to develop/use the latest machine learning strategies and computational analytics to analyze genomic and multimodal data to enable novel insights into biology and human health.

Principal investigators will be able to leverage GIS' strong sequencing facility, technology platforms, novel computational analytics, and outstanding biological systems to create scientific and societal impact.

Qualified candidates should have an MD, PhD, or equivalent degree in the biological, genomic, or computational sciences, and a demonstrated ability to conduct cutting-edge team-based research with a strong record of peer-reviewed publications, and external funding. Past successes in intellectual property creation will be an advantage. You must be comfortable working in a dynamic research organization. Strong communication skills and a willingness to work collaboratively in a multidisciplinary environment are critical for success. The successful candidate will drive an expansion into the indicated research areas and complement programs at GIS and synergise with ongoing larger-scale efforts at A-STAR. In particular, we welcome applications from energetic and enthusiastic candidates seeking their first independent Principal Investigator position (equivalent to first-time Assistant Professor at academic institutions).

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-%28Data-driven-understanding-of-hydroclimate-extremes%29/33189-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Applications are requested for Research Engineer (RE) positions on climate change, risk assessment of compound droughts and floods using the latest AI techniques in the Department of Civil and Environmental Engineering at the National University of Singapore (NUS).

The selected Research Engineer (RE) is required to work on:
•    drought and flood risk assessment under climate change.
•    land use optimization and reservoir-informed managed aquifer recharge assessment. 
•    multi-sector dynamics. 

Job Requirements

•    At least a bachelor’s degree in civil engineering, hydrology, water resources engineering, optimization, seasonal forecasting, machine learning, or from similar programs.
•    Master’s degree is preferred.
•    Extensive experience in developing complex computer codes, e.g. in Python, R, or Shell.
•    Ability to construct and write papers for leading research journals and conferences. 
•    Good written and spoken communication.
•    Open to fixed-term contract. 

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

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Engineer-%28Data-driven-understanding-of-hydroclimate-extremes%29/33190-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Applications are requested for Research Engineer (RE) positions on climate change, risk assessment of compound droughts and floods using the latest AI techniques in the Department of Civil and Environmental Engineering at the National University of Singapore (NUS).

The selected Research Engineer (RE) is required to work on:
•    drought and flood risk assessment under climate change.
•    land use optimization and reservoir-informed managed aquifer recharge assessment. 
•    multi-sector dynamics. 

Job Requirements

•    At least a bachelor’s degree in civil engineering, hydrology, water resources engineering, optimization, seasonal forecasting, machine learning, or from similar programs.
•    Master’s degree is preferred.
•    Extensive experience in developing complex computer codes, e.g. in Python, R, or Shell.
•    Ability to construct and write papers for leading research journals and conferences. 
•    Good written and spoken communication.
•    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-Centrifuge-Modelling%29/33193-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The selected Research Fellow (RF) will be responsible for leading and managing research activities related to the project titled “Offshore Centrifuge modelling.” 

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. 
•    Has 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 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-%28Quality-Assurance%29/33198-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The National University of Singapore invites applications for Research Assistant (Quality Assurance (QA) Executive) in the Clinical Imaging Research Centre (CIRC), Yong Loo Lin School of Medicine. CIRC is a dedicated molecular imaging research centre. It is equipped with on-site capability for the preparation of PET radiopharmaceuticals in a state-of-the-art GMP-certified facility. CIRC is positioned to support both academic and commercially led clinical research programs, with dedicated clinical imaging facilities area advanced modalities of PET-CT and PET-MRI. For more details on what we do, do visit https://medicine.nus.edu.sg/circ/. Appointments will be made on a two-years contract basis with the possibility of extension.

Purpose of the post

This role provides QA support across document control, batch record management, training records, supplier documentation, audits, and quality system activities. Responsibilities include maintaining quality registers, tracking due dates and CAPA actions, supporting Bizzmine eQMS document control, checking Batch Manufacturing Records for completeness, and assisting with QA reporting and trending. Also supports GMP training, supplier qualification records, inspection readiness, and maintenance of key controlled documents. In addition, the role contributes to QA improvement work and is being trained to support investigational radiopharmaceutical release as an Authorised Person under supervision.

Main duties and responsibilities

The QA Executive will be able to:

1. Provide OMS Support – maintain and update registers
2. Assist in document management & eQMS (Bizzmine)
3. Support Batch Record (BMR) & QA Operations
4. Assist, arrange & support training and filing of training records, especially the annual GMP training
5. Assist & support in maintaining supplier and material documentation
6. Assist & support during audit & inspection period
7. Assist in QA related improvement projects and digital quality system activities
8. To take up the role of Authorised Person for the release of investigational radiopharmaceuticals in compliance with PIC/S GMP (Under supervision)

Qualifications

The applicant should:

1. Have a minimum of bachelor’s degree (Honours) or higher in Pharmaceutical Science, Chemistry, Life Sciences or related discipline;
2. Previous experience working in a PET radiochemistry facility is highly desirable. 
3. Typically, 1-3 years of relevant experience in QA/QC/QMS in a regulated environment (GMP/PIC/S GMP experience is strongly preferred). 
4. Excellent understanding of radiochemical and radiopharmaceutical processes, including material flows, quality controls, and critical parameters in GMP environments. 
5. Strong organizational and project planning skills, with the ability to manage multiple tasks and priorities in a regulated environment. 
6. Working knowledge of GMP principles and their application to equipment qualification, maintenance, and facility operations. 
7. Understanding of radiation safety principles and engineered controls for radioactive materials. 
8. Excellent communication and teamwork skills, with a collaborative approach to problem-solving across scientific, quality, and engineering disciplines. 
9. Working knowledge of PIC/S GMP and good documentation practices (GDP). 
10. Strong coordination skills; able to follow up across teams and manage multiple deadlines. 
11. Comfortable working with digital systems (experience with eQMS is advantageous). 
12. Clear written communication, with strong attention to detail and integrity in a GMP environment 
13. Need to be adaptable and flexible to perform required tasks beyond the job description 
14. Willing to accept exposure of low radiation levels (radiopharmaceutical manufacturing) & enter clean room/rotational function.

Remuneration will be commensurate with the candidate’s qualifications and experience. Informal enquiries are welcome and should be made to Ms Emmalyn Chan Mei Mei at emma.chan@nus.edu.sg.

Formal application: Please submit your application, indicating current/expected salary, supported by a detailed CV (including personal particulars, academic and employment history, complete list of publications/oral presentations and full contacts of three (3) referees to the NUS Career Portal.

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-Associate-%28Cracks-in-Clays%29/33195-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are hiring a Research Associate (RA) to study the desiccation induced crack in clay barriers.

The selected RA is required to:
 •    Develop a phase field model considering elastoplasticity and absorption.
•    Extend to make the complex thermo-hydro-mechanical-chemical environment with application to practice.

Job Requirements

•    Possess at least a master’s degree in relevant field.
•    At least 2 years or more of relevant work experience. 
•    Has demonstrated research or professional background that aligns with the development of the topic.
•    Experience in multiple areas is highly desirable.
•    Exhibit proficiency in coupled multi-phase modelling and phase field modelling.
•    Display strong teamwork capabilities.
•    Effective communication skills; written and spoken.
•    Please note that only shortlisted candidates will be contacted.
•    Open to fixed-term contract.

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-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

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!