School of Medicine Established in 1930, Duke University School of Medicine is the youngest of the nation's top medical schools. Ranked sixth among medical schools in the nation, the School takes pride in being an inclusive community of outstanding learners, investigators, clinicians, and staff where interdisciplinary collaboration is embraced and great ideas accelerate translation of fundamental scientific discoveries to improve human health locally and around the globe. Composed of more than 2,500 faculty physicians and researchers, more than 1,300 students, and more than 6,000 staff, the Duke University School of Medicine along with the Duke University School of Nursing, Duke University Health System and the Private Diagnostic Clinic (PDC) comprise Duke Health. a world-class academic medical center. The Health System encompasses Duke University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Primary Care, Duke Home and Hospice, Duke Health and Wellness, and multiple affiliations.
Position Summary:
The Department of Biostatistics & Bioinformatics (B&B) at the Duke University School of Medicine engages in methodological and collaborative research, providing international and regional leadership in biostatistics, genomics, biomedical informatics, artificial intelligence and health data science. We are recruiting a creative, rigorous Postdoctoral Research Scientist in Dr. Wenpin Hou’s team to design and deploy new methods on large-scale datasets (e.g., NIH-funded and consortia resources). Dr. Wenpin Hou develops AI and statistical methods to decode gene regulatory programs from large-scale single-cell and spatial multiomics data. Her research aims to characterize developmental processes, uncover regulatory alterations in complex human diseases, and identify actionable targets for therapeutic intervention. Dr. Hou collaborate across Duke University, Columbia University, UC Santa Cruz, and Johns Hopkins to advance understanding of gene regulation, cellular mechanisms, and human health. Dr. Hou’s group has designated access to high-performance computing (H100 and H200 GPUs).
Key Responsibilities:
* Lead and co-lead projects in AI for genomics (e.g., generative models, transformers, agentic workflows) and/or statistical learning (e.g., network & spatiotemporal modeling, functional/longitudinal data, time-series).
* Analyze single-cell/spatial multi-omics and epigenomic data in applications spanning development, cancer, neurodegeneration, and immunology.
* Publish in top venues, present at major conferences, and contribute to open-source software.
* Receive tailored mentorship in grant writing (e.g., NIH K99/R00), career planning, and leadership.
Minimum Qualifications: The candidate should hold a PhD (or equivalent) in Computer Science, Biostatistics/Statistics, Bioinformatics, Computational Biology, Mathematics, Biomedical Engineering, or a related field by the start date.
We welcome candidates grounded in one or more of the following:
Generative AI/transformers, agentic AI, deep learning
Computational genomics, network modeling, spatiotemporal/functional data analysis, time-series
Strong programming in R and/or Python; best practices in reproducible research
Excellent communication, independence, and collaboration skills
Please email the following materials directory to Dr. Hou