Research Fellow (Maritime Decarbonization)

NATIONAL UNIVERSITY OF SINGAPORE; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

A prominent educational institute in Singapore seeks a full-time Research Fellow for the PRECISE-SG100K project. The role focuses on analyzing and integrating large-scale proteomics data with genomic information to drive research on disease mechanisms and biomarker discovery. Ideal candidates should hold a PhD in a relevant field and possess strong experience in proteomics and data analysis. The position involves collaboration with multidisciplinary teams, contributing to impactful research outcomes.

Qualifications

• Strong background in proteomics data analysis or other omics domains.
• Experience with large-scale cohorts or biobanks is beneficial.
• Familiar with genetic association testing and multi-omics pipelines.

Responsibilities

• Develop research questions and analysis plans using EMR-derived data.
• Perform quality control and standardisation workflows.
• Conduct pQTL mapping and apply statistical genetics methods.
• Collaborate with biologists, clinicians, and bioinformaticians.
• Lead manuscript preparation and grant-related tasks.

Skills

Data analysis tools proficiency (R, Python, SQL)

Strong communication skills

Highly organized

Education

PhD in Biostatistics, Bioinformatics, Statistical Genetics, or related fields

Tools

Statistical genetics tools

Cloud environments

Nextflow

Job description

Interested applicants are invited to apply directly at the NUS Career Portal.

Your application will be processed only if you apply via the NUS Career Portal.

We regret that only shortlisted candidates will be notified.

Job Description

Research Fellow (Proteomics for PRECISE‑SG100K)

We are seeking a full‑time Research Fellow to join our team at the Saw Swee Hock School of Public Health (SSHSPH), National University of Singapore (NUS). NUS is a leading global institution known for high‑impact research, innovative education, and thought leadership. SSHSPH works closely with government agencies, healthcare institutions, and international partners to develop evidence‑based solutions that inform policy and advance public health in Singapore and the region. SSHSPH provides a dynamic, interdisciplinary environment that supports collaboration, professional growth, and impactful scholarship.

The SG100K project is a unique multi‑ancestry population cohort dataset of roughly 100,000 citizens and permanent residents living in Singapore drawn from four major prospective population cohorts. Detailed research phenotyping, including health and lifestyle information and physical examination, were performed at recruitment. In partnership with PRECISE, whole genomes at 30× depth were generated for these individuals. The PRECISE‑SG100K resource, comprising of the research phenotype data and whole genomes, has been linked to individual electronic health records at the TRUST platform (https://trustplatform.sg/). Large‑scale proteomics data have also been generated for these individuals.

We are inviting a motivated Research Fellow to join our PRECISE‑SG100K collaboration to work on the dataset, specifically on the proteomics data. The Research Fellow will drive proteomics and pQTL research within a multidisciplinary team focused on understanding protein variation, molecular mechanisms of disease, and biomarker discovery. The role involves generating, analysing, and integrating large‑scale proteomics datasets with genomic and clinical data, contributing to high‑impact publications and translational research outcomes.

Job Scope

• Develop research questions, study designs, and analysis plans using EMR‑derived data.
• Perform quality control and develop or adapt standardisation/normalisation workflows for high‑throughput analyses.
• Conduct pQTL mapping and apply statistical genetics methods (e.g., GWAS, QTL mapping, colocalisation, Mendelian randomisation).
• Work closely with biologists, clinicians, bioinformaticians, and statisticians.
• Develop documentation, codebooks, or tools to support reproducible research.
• Lead manuscript preparation, conference presentations, and grant‑related deliverables.

Requirements

• Strong experience with proteomics data or other omics data.
• Proficiency in data analysis tools (e.g., R, Python, SQL) or statistical genetics tools.
• Strong written and verbal communication skills.
• Highly organised and able to work effectively independently as well as with a team.

Preferred Qualifications

• Experience with large‑scale cohorts or biobanks.
• Familiarity with imputation, genetic association testing and multi‑omics processing and pipelines.
• Experience with cloud environments and workflow managers such as Nextflow.
• Experience working with secure research environments (e.g., TREs, data enclaves).

Application Documents

• Cover letter highlighting relevant experience and how they meet the selection criteria.
• Curriculum Vitae, containing names and contact details of three named referees.

Qualifications

• PhD in Biostatistics, Bioinformatics, Statistical Genetics, or related fields.