PhD Student

We are looking for PhD students with strong quantitative thinking and interest in computational biology, metabolomics, microbiome, bioinformatics, machine learning, statistics, or biomedical data science.

Good background

• Bachelor's or Master's degree in bioinformatics, computational biology, computer science, statistics, biomedical engineering, analytical chemistry, life sciences, medicine, or a related area.
• Experience with R or Python, reproducible data analysis, and clear scientific writing.
• Interest in multi-omics integration, LC-MS data analysis, microbiome-metabolome interaction, causal inference, or AI for biomedical research.

Admissions and funding

PhD applicants should apply through the LKCMedicine PhD by Research Programme. Typical planning should consider January and August intakes, but exact deadlines and eligibility must follow LKCMedicine and NTU Graduate Admissions.

LKCMedicine lists core admission criteria including a strong Bachelor's degree, confirmation from a proposed supervisor, English proficiency requirements, and optional but encouraged GRE for applicants who are not graduates of Singapore autonomous universities.

Research Fellow

We welcome postdoctoral researchers who can lead independent projects and collaborate across computational and biomedical teams.

Expected profile

• PhD in bioinformatics, computational biology, statistics, computer science, metabolomics, microbiome research, systems biology, analytical chemistry, or related fields.
• Strong publication record and ability to move a project from data to method, result, manuscript, and reusable software.
• Experience in AI/ML, causal inference, knowledge graphs, pathway analysis, LC-MS workflows, microbiome data analysis, or multi-omics integration is especially relevant.

Fellowship routes

Candidates with independent fellowship plans are strongly encouraged to contact us early. Suitable schemes may include the NTU AI-for-X Postdoctoral Fellowship, Presidential Postdoctoral Fellowship, Lee Kuan Yew Postdoctoral Fellowship, and Schmidt AI in Science Postdoctoral Fellowship.

Undergraduate Student

NTU undergraduates are welcome to discuss research projects through URECA, FYP, credit-bearing research, or informal research attachments.

• Suitable for students interested in omics data analysis, AI for biology, reproducible programming, web tools, or biomedical data visualization.
• Prior R/Python experience is helpful but not mandatory if you are motivated to learn carefully.
• Projects can be scoped from method benchmarking to software development and biological data analysis.

Visiting Scholar

We welcome visiting scholars whose research interests align with the lab. Visitors are expected to have external funding or institutional support covering salary, travel, visa, insurance, and living expenses.

• Please send a CV, proposed visit period, funding source, and a short research plan.
• Projects should have a clear computational or multi-omics component and a realistic output plan.

Visiting PhD Student

Visiting PhD students are welcome when there is a good match with ongoing projects and external funding is available. Examples may include CSC or university-sponsored visiting PhD schemes.

• Please contact us with your CV, current PhD topic, advisor information, expected visiting period, funding plan, and a one-page proposal.
• Good fits include multi-omics integration, metabolomics/microbiome analysis, pathway interpretation, biomedical AI, and scientific software.

Summer Intern

We host selected summer interns, including remote interns, when a project is well defined and mentoring capacity is available.

• Best suited for students who can commit to a focused project for several weeks or months.
• Remote projects usually require stronger independence, regular progress updates, and clear coding or analysis deliverables.
• Send a CV, transcript if available, GitHub or prior project links, and a short statement of what you want to learn.