Job Description: Postdoctoral Research Fellow
About Duke-NUS Medical School:
Duke-NUS Medical School is a premier research and graduate medical school in Singapore, established through a strategic partnership between Duke University in the United States and the National University of Singapore (NUS) in Singapore. This unique partnership leverages Duke’s expertise in medical education and NUS’s world-class research infrastructure to foster innovation at the interface of biomedical research and clinical care.
Position Overview:
Dr. Xiaoyu Song’s lab in Centre for Biomedical Data Science at Duke-NUS Medical School is seeking a highly motivated Postdoctoral Research Fellow with expertise in computer science, biostatistics, statistics, bioinformatics, computational biology or other AI-related fields. The successful candidate will join a dynamic and interdisciplinary team focusing on the development and application of novel AI and statistical methods for multi-omics data analysis. Potential projects may include developing AI and statistical methods for single-cell and spatial proteomics, tumor microenvironment studies on spatial transcriptomics, cell-type-aware association analysis of bulk omics data, and cancer proteogenomics integrative analysis. This position offers a unique opportunity to work at the forefront of biomedical data sciences, contributing to discoveries that impact the understanding of cancer, cardiometabolic diseases, neurodegeneration, and other complex diseases. Dr. Xiaoyu Song’s profile is as follow: https://sites.google.com/view/xiaoyu-song/home.
Key Responsibilities:
The postdoctoral researcher will engage in both independent and collaborative research, driving innovative projects at the intersection of statistics and biomedical sciences. He/she is expected to plan, organize, conduct, communicate, and disseminate research studies within the overall scope of a research project at Duke-NUS. Their responsibilities include:
Method Development: 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.
Data Analysis: Analyze large-scale omics datasets, interpret results, and generate biological insights.
Collaboration: Work closely with national and international collaborators, including biostatisticians, clinicians, biologists, students and other research staff.
Presentation: Prepare oral presentations and written reports to evaluate data, explain analysis methods, and interpret results.
Manuscript Preparation: Lead and contribute to high-impact publications in statistical and biomedical journals.
Grant Writing: 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.
Qualifications:
PhD in Computer Science, Biostatistics, Statistics, Bioinformatics, Computational Biology, or other AI-related fields.
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 record in peer-reviewed journals is an advantage.
Experience with biological data (e.g., genomics, transcriptomics, single-cell data) is an advantage.
What We Offer:
Access to state-of-the-art resources in biomedical research at Duke-NUS Medical School.
Opportunities to collaborate with leading scientists globally through NIH and NUS networks.
Mentorship for career development and support in transitioning to academic independence.
Competitive salary and benefits, commensurate with experience.
Contact: song.xiaoyu@duke-nus.edu.sg