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Research Fellow (CBDS/SXY)

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National University of Singapore (NUS)

Outram Campus

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Research Fellow (CBDS/SXY)

Research Fellow

29 June 2026

Location

Outram Campus

Duke-NUS Medical School

Type

Full-time Staff

Required Qualifications

PhD in Biostatistics, Bioinformatics, Statistics, or related
Proficiency in R and/or Python
Statistical modelling, machine learning, high-dimensional data analysis
Experience in metabolomics or omics data preferred

Research Areas

Metabolomics and multi-omics analysis
Cardiovascular and metabolic diseases
Biostatistics and AI methods
Translational medicine and biomarkers
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Research Fellow (CBDS/SXY)

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.

Prof. Wang Yibin and Dr. Xiaoyu Song are seeking a highly motivated Research Fellow to join a collaborative, interdisciplinary team focused on statistical, computational, and integrative analysis of metabolomics and other omics data, with applications in cardiovascular and metabolic diseases. The successful candidate will contribute to interdisciplinary research at the interface of biostatistics, bioinformatics, computational biology, and metabolomics, with applications in translational cardiovascular science. Projects may include developing and applying statistical and AI methods for metabolomics and spatial multi-omics data, integrating multi-modal datasets (genomic, transcriptomic, proteomic, and clinical), and identifying molecular mechanisms, biomarkers, and risk predictors for cardiovascular and metabolic diseases.

This position offers a unique opportunity to work closely with both methodological and biomedical investigators in a highly collaborative environment, and to contribute to impactful research in human disease biology and translational medicine.

Key Responsibilities:

  • Design, adapt, and apply statistical, computational, or AI-based methods for metabolomics and multi-omics data analysis.
  • Analyse large-scale metabolomics, proteomics, transcriptomics, genomics, imaging, and clinical datasets; interpret results to generate biological and/or clinical insights.
  • Contribute to integrative analyses to elucidate molecular mechanisms and identify biomarkers for cardiovascular and metabolic diseases.
  • Work closely with biostatisticians, clinicians, biologists, and other collaborators within Duke-NUS and with external partners.
  • Prepare oral presentations, written reports, and visual summaries to communicate methodologies, findings, and scientific significance.
  • Contribute to and lead preparation of manuscripts for submission to statistical, computational, and biomedical journals.
  • Assist in the preparation of grant applications, progress reports, and related research documentation.
  • Support project coordination and maintain well-organised documentation of research activities.
  • Perform any other related duties incidental to the work described herein.

Job Requirements

  • PhD in Biostatistics, Bioinformatics, Computational Biology, Statistics, Data Science, Systems Biology, or a related quantitative field.
  • Strong background in statistical modelling, machine learning, bioinformatics, or high-dimensional data analysis.
  • Proficiency in programming languages such as R and/or Python.
  • Experience in the analysis of metabolomics, spatial omics, or other biomedical datasets is preferred.
  • Interest in cardiovascular biology, metabolic disorders, translational medicine, or biomarker discovery is desirable.
  • Excellent communication, organisational, and collaborative skills.
  • Ability to work both independently and as part of an interdisciplinary research team.
  • A strong publi

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Frequently Asked Questions

🎓What qualifications are required for this Research Fellow position at Duke-NUS?

Candidates must hold a PhD in Biostatistics, Bioinformatics, Computational Biology, Statistics, Data Science, or a related quantitative field. A strong background in statistical modelling, machine learning, and high-dimensional data analysis is essential, along with proficiency in R and/or Python. Experience with metabolomics, spatial omics, or biomedical datasets is preferred. Excellent communication and collaborative skills are required. Learn more about thriving in research roles via our guide on postdoctoral success. Explore research jobs.

🔬What are the key responsibilities of the Research Fellow?

Responsibilities include designing and applying statistical, computational, AI-based methods for metabolomics and multi-omics data analysis; analyzing large-scale datasets (genomics, transcriptomics, proteomics, clinical); contributing to biomarker discovery for cardiovascular and metabolic diseases; collaborating with interdisciplinary teams; preparing presentations, manuscripts, and grant applications. See related opportunities in research assistant jobs.

📊What is the research focus of this Duke-NUS Research Fellow role?

The role focuses on integrative analysis of metabolomics and omics data for cardiovascular and metabolic diseases, developing AI methods for spatial multi-omics, integrating multi-modal datasets, and identifying molecular mechanisms and biomarkers. Work with Prof. Wang Yibin and Dr. Xiaoyu Song in a collaborative environment at the Centre for Biomedical Data Science (CBDS). Check clinical research jobs for similar positions.

📝How do I apply for this Research Fellow position?

Applications are open until 29 June 2026. Submit via the Duke-NUS portal linked in the job post. Prepare a CV highlighting omics analysis experience and publications. Tailor your academic CV using our guide to writing a winning academic CV. Visit postdoc jobs for more listings.

💻What skills and experience are preferred for success in this role?

Preferred skills include experience in metabolomics, spatial omics, or biomedical data analysis, interest in cardiovascular biology, metabolic disorders, and biomarker discovery. Strong programming in R/Python and ability to work independently in interdisciplinary teams are key. Build your profile with tips from excelling as a research assistant.

📍Where is the position located and what is the employment type?

Located at Outram Campus, Duke-NUS Medical School, Singapore. This is a full-time staff position in Laboratory and Research, classified under Staff/Administration. Ideal for those seeking research fellow jobs in bioinformatics. Browse research jobs in Singapore.

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