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.


• Multidisciplinary academic or research background.

Other Requirements

• 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.

Be Bold.

Key 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.

Choose Duke.

Join a world-class research environment at Duke University, where innovation, discovery, and collaboration drive advances in human health. The Zhang Lab develops novel computational and quantitative approaches to understand complex biological systems, integrating machine learning, biophysics, and genomics to address important questions in tissue biology and disease.

As part of Duke's vibrant research community, you will work alongside leading investigators and trainees, gain exposure to cutting-edge technologies and datasets, and contribute to impactful scientific discoveries with opportunities for publication and professional growth. This position is fully grant-funded.

Learn more about Duke University's competitive benefits package and commitment to excellence, innovation, and inclusion.

Screening of Applications

Screening continues until the position is filled.

 

Work requires two years of experience in research/data analysis or related position. OR AN EQUIVALENT COMBINATION OF RELEVANT EDUCATION AND/OR EXPERIENCE