Director Bioinformatics Genetics Jobs in Raleigh, NC

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.

Bioinformatician II - Cancer Genomics & Single-Cell Biology

The Oliver Lab at Duke University (www.theoliverlab.com) is seeking a highly motivated Bioinformatician II to join a multidisciplinary research team focused on understanding the mechanisms that drive tumor lineage plasticity, heterogeneity, and drug resistance in lung cancer. Building on recent discoveries (Finlay et al, Cancer Cell, 2024 and Ireland et al., Nature, 2025), our work integrates advanced computational and experimental approaches to define how tumors evolve under therapeutic pressure.

This position offers the opportunity to work at the interface of cancer biology, genomics, and data science, leveraging large-scale datasets from genetically engineered mouse models, organoid systems, and human tumor specimens. The successful candidate will play a central role in analyzing and integrating single-cell, spatial transcriptomic, and multi-omic datasets to uncover new biological insights and therapeutic vulnerabilities.

Minimum Requirements: 

• PhD in Bioinformatics, Computational Biology, Genomics, Computer Science, or a related field (or MS with substantial relevant experience) 
• Strong programming skills (e.g., Python, R, or equivalent) 
• Experience analyzing high-dimensional genomic data, particularly RNA-seq or single-cell datasets 
• Demonstrated ability to work independently and flexibly manage multiple projects 
• Strong communication skills and ability to collaborate in a team-oriented environment 

Preferred Qualifications: 

• Experience with single-cell and/or spatial transcriptomics analysis 
• Familiarity with multi-omics data integration 
• Experience applying machine learning or statistical modeling to biological datasets 
• Experience working in cancer biology or related biomedical fields 
• Experience with high-performance computing environments and reproducible workflows 

Be Bold.                                         

• Lead and contribute to the analysis of single-cell RNA-seq, spatial transcriptomics, and multi-omic datasets from mouse and human cancer models 
• Develop and implement computational pipelines for large-scale genomic data analysis and integration 
• Apply statistical and machine learning approaches to identify cell states, lineage relationships, and mechanisms of therapy resistance 
• Collaborate closely with experimental biologists to design analyses, interpret results, and guide hypothesis generation 
• Contribute to manuscript preparation, grant applications, and presentation of findings at scientific meetings 
• Mentor trainees and contribute to a collaborative and interdisciplinary research environment 

 

Choose Duke.                                                                                                                                                                                                                                                          

• Work on cutting-edge questions in cancer biology with direct relevance to therapy resistance and precision medicine 
• Access to rich, multi-modal datasets from state-of-the-art experimental systems and human tumors 
• Collaborative, interdisciplinary environment integrating computational and experimental approaches 
• Strong track record of high-impact publications and career development for trainees