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.

Dr. Song Xiaoyu's laboratory is seeking a highly motivated Research Fellow with expertise in computer science, biostatistics, statistics, bioinformatics, computational biology, or other AI-related disciplines. The successful candidate will join a dynamic, interdisciplinary team focusedon developing and applying novel AI and statistical methods for multi-omics data analysis. This position offers a unique opportunity to work at the forefront of biomedical data science and contribute to discoveries that advance the understanding of cancer, cardiometabolic diseases, neurodegeneration, and other complex conditions.

More information about Dr Song Xiaoyu can be found at https://sites.google.com/view/xiaoyu-song/home.

Key Responsibilities:

The Research Fellow will undertake both independent and collaborative research, driving innovative projects at the intersection of statistics/AI and biomedical sciences. He/She will be responsible for planning, organising, executing, and communicating research activities within the overall scope of research initiatives at Duke-NUS.

• Design and develop AI and statistical methods for complex omics data, including multi-modality (e.g. DNA, RNA, protein, PTM, metabolites) in different resolutions (e.g. subject, tissue, single cell) with or without spatial features.
• Analyse large-scale omics datasets, interpret results, and generate biological insights.
• Work closely with national and international collaborators, including clinicians, biologists, computer scientists, biostatisticians, students and other research staff.
• Prepare oral presentations, posters, and written reports to evaluate data, explain analysis methods, and interpret results.
• Lead and contribute to high-impact publications in statistical and biomedical journals.
• Assist in the preparation of grant applications and reports for ongoing funded projects. Develop skills and experience to write mentored and independent research grants.
• Perform other related duties incidental to the work described herein.

Job Requirements

• PhD in Computer Science, Biostatistics, Statistics, Bioinformatics, Computational Biology, or other AI-related disciplines.
• Strong foundation in AI, statistical modeling, machine learning, or high-dimensional data analysis.
• Proficiency in programming languages such as R, Python, or Julia.
• Excellent communication and collaborative skills.
• Strong publication records in peer-reviewed journals is an advantage.
• Experience with biological data (e.g., genomics, transcriptomics, single-cell data) is an advantage.

We regret that only shortlisted candidates will be notified.