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 2,600 faculty physicians and researchers, nearly 2,000 students, and more than 6,200 staff, the Duke University School of Medicine along with the Duke University School of Nursing, and Duke University Health System comprise Duke Health, a world-class academic medical center. The Health System encompasses Duke University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and multiple affiliations. Be You. The Yi Zhang Lab in the Department of Biostatistics & Bioinformatics at Duke University is seeking a Research Analyst I to join a cutting-edge research program focused on biophysics-inspired computational modeling and genomics data analysis. This is an excellent opportunity for a recent graduate with a strong quantitative background to gain hands-on research experience at the intersection of computational biology, machine learning, and tissue biology. In this role, you will work closely with Dr. Yi Zhang and collaborators to develop and apply computational methods for analyzing complex biological data, including spatial transcriptomics and other genomics datasets. You will participate in innovative research projects, contribute to scientific publications, and receive mentorship and career development training within a collaborative and supportive research environment. This project is expected to last approximately 6 months to 1 year. Minimum Requirements Bachelor's degree in a quantitative field obtained within the last 12 months. Degree in Computational Biology, Mathematics, Physics, Data Science, Computer Science, Biomedical Engineering, Electrical Engineering, Bioinformatics, Biophysics, or a related discipline. Demonstrated programming experience in Python and Linux-based computing environments. Ability to work collaboratively in a research setting and communicate scientific findings effectively. Preferred Qualifications Strong computational and data analysis skills with experience developing analytical methods. Experience with machine learning, deep learning, graph-based models, variational autoencoders, or physics-inspired computational approaches. Familiarity with genomics, single-cell genomics, or spatial omics data analysis. Experience using scientific computing and machine learning frameworks such as PyTorch. Experience contributing to open-source software repositories. Strong scientific writing, presentation, and communication skills. Mu
