Research Fellow (OR/EID/ML3)
Job Description
The Signature Research Programme in Emerging Infectious Diseases (EID) aims to pioneer our understanding of emerging infections through world-class research that integrates immunology, infection biology, pathogen genomics, and computational approaches. This integration drives comprehensive studies of host–pathogen interactions across molecular, individual, and population scales to address emerging health challenges.
The Coronavirus Lab, led by Assistant Professor Mart Lamers within the Signature Research Programme in Emerging Infectious Diseases (EID), is seeking a full-time Research Fellow / Senior Research Fellow in Computational Biology. Our group leverages cutting-edge technologies—including organoids, CRISPR/Cas9, single-cell and spatial omics—to study coronavirus–host interactions that influence pandemic potential and disease pathogenesis.
We welcome applications from candidates with a strong background in computational and quantitative biology. The successful candidate will play a key role in analysing high-dimensional datasets and fostering an interdisciplinary research environment at the interface of virology, genomics, and data science.
We are looking for a creative, innovation-driven individual who is eager to uncover hidden patterns within complex datasets—insights that can both strengthen our experimental findings and spark bold, testable hypotheses that push the boundaries of discovery in our lab. This role also offers the freedom to develop quantitative AI/ML pipelines for pathogen risk assessment, informed by insights from our wet lab scientists.
Main Responsibilities
- Perform tasks and support all aspects of the research project.
- Carry out algorithm development and data analysis, including (but not limited to) single-cell and bulk transcriptomics, spatial omics, proteomics, and genome-wide association (GWAS) data independently.
- Lead AI/ML-driven efforts to develop pathogen risk assessment pipelines.
- Collaborate with experimental scientists to integrate computational findings with biological hypotheses.
- Contribute to scientific writing and dissemination of results through publications, presentations, and grant proposals.
- Mentor junior lab members and contribute to collaborative team science efforts.
- Perform other related duties incidental to the work described therein.
Job Requirements
- PhD Degree in a related scientific area (e.g., Bioinformatics, Computational Biology, Machine Learning/AI, Computer Science, Virology, Cell biology, or Immunology) with demonstrated hands-on experience in developing and/or applying algorithms for multi-omics data integration.
- Proven proficiency analysing bulk and single-cell transcriptomic datasets.
- Proficiency in R and/or Python coding.
- Familiarity with high-performance computing (HPC) environments and GPU programming.
- Have experience with spatial omics or GWAS analysis is strongly advantageous.
- Experience with AI/ML approaches for biological data analysis would be advantageous.
- Have excellent quantitative, analytical, and organizational skills.
- Collaborative, motivated, and adaptable, with a commitment to open and integrative team science.
We regret that only shortlisted candidates will be notified.
University-Level Unit: Duke-NUS Medical School
Faculty/Department-Level Unit: Office of Research
Employee Category: Research Staff
Location: Outram Campus
Posting Start Date: 11/05/2026