Research Fellow (OR/CBDS/FQ)

National University of Singapore; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

Duke-NUS Medical School in Singapore seeks a Research Fellow to contribute to integrative genomics and multimodal biological data analysis, with applications in ocular disease and other complex diseases.

You will work under the supervision of Dr. Qiao FAN, access high-performance computing, and collaborate with SingHealth researchers to advance data-driven discoveries.

This role offers growth through diverse projects, academic publication opportunities, and a competitive research stipend.

Qualifications

• PhD in Biostatistics, Computational Biology, Bioinformatics, Genetic Epidemiology, or a related field.

Responsibilities

• Develop advanced statistical and machine learning modeling to conduct data analyses for large-scale multimodal studies.
• Conceptualise new ideas and lead data-driven discoveries with in-depth results interpretation.
• Conduct analyses on large-scale clinical and biobank data, including whole-exome sequencing and omics data.
• Write high-quality research papers, present findings, and collaborate with local/international researchers.
• Assist in grant writing and reports for funded projects.
• Mentor graduate students and junior researchers.
• Perform other related duties incidental to the work described therein.

Skills

Statistical modelling

Machine learning

Genomics data analysis

Multimodal data analysis

Biobank data analysis

R

Python

Perl

Linux

Education

PhD in Biostatistics, Computational Biology, Bioinformatics, Genetic Epidemiology, or related field

Tools

R

Python

Perl

Linux

Job description

University-Level Unit: Duke-NUS Medical School

Faculty/Department-Level Unit: Office of Research

Employee Category: Research Staff

Posting Start Date: 04/09/2026

Job Description

The Duke-NUS Centre for Biomedical Data Science (CBDS) serves as a central hub for Duke-NUS faculty specialising in Biostatistics, Bioinformatics, Systems Biology, Artificial Intelligence (AI), and other quantitative and data-driven sciences. CBDS functions as a strategic platform for cutting-edge research, education, and services in data science, AI, and biomedical computation, building on existing institutional initiatives such as DAISI.

We are seeking a highly motivated and talented Research Fellow to contribute to integrative genomics and multimodal biological data analysis, with applications in ocular disease and other complex diseases. This is a unique opportunity to contribute to high-impact science in a world-class academic medical centre, in collaboration with SingHealth —Singapore’s largest healthcare network. The successful candidate will participate in diverse research projects under the supervision of Dr. Qiao FAN.

Why Join Us?

• Access to cutting-edge datasets, a collaborative research ecosystem, and high-performance computing.
• Opportunities for career growth, international collaborations, and high-impact publications.
• 2-year appointment, with potential for extension subject to performance and fund availability.

Responsibilities

• Develop advanced statistical and machine learning modeling to conduct data analyses for large-scale multimodal (genomics, omics etc) studies.
• Conceptualise new ideas, lead data-driven discoveries, ensuring in-depth assessment and interpretation of results.
• Conduct efficient data analyses on large-scale clinical and biobank data, including (but not limited to) whole-exome sequencing and omics data.
• Write high-quality research papers, present research findings, and foster collaboration with local and international researchers.
• Assist in grant writing and reports for ongoing funded projects.
• Mentor graduate students and junior researchers in a dynamic environment.
• Perform other related duties incidental to the work described therein.

Job Requirements

• PhD in Biostatistics, Computational Biology, Bioinformatics, Genetic Epidemiology, or a related field.
• Strong experience in statistical modelling, machine learning/deep learning, genomics and multimodal biological, and biobank data analysis.
• Proficiency in R, Python, Perl, and Linux environments.

  We regret that only shortlisted candidates will be notified.