Research Analyst I

About the role

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. The project is expected to last approximately 6 months to 1 year.

Responsibilities

• Develop computational models using Python and PyTorch, including graph‑based learning approaches, variational autoencoders, and biophysics‑inspired computational frameworks.
• Analyze genomics and spatial transcriptomics datasets to investigate gene expression patterns, tissue organization, and disease‑related biological processes.
• Conduct computational experiments by training models, optimizing parameters, benchmarking methods, and evaluating analytical performance.
• Review, reproduce, and implement published methods from computational genomics, machine learning, biophysics, and cancer biology literature.
• Document and communicate research findings through reproducible code, data analysis workflows, scientific presentations, and contributions to manuscripts for peer‑reviewed publication.

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.
• Work requires two years of experience in research/data analysis or a related position, OR an equivalent combination of relevant education and/or experience.
• Position is fully grant‑funded.
• No supervisory responsibilities.
• Works under the guidance of the Principal Investigator and senior laboratory personnel.
• Commitment to maintaining reproducible research practices and documentation.
• Work Location: Onsite.

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,