Associate in Research

Associate in Research

Work Arrangement:
On-Site

Requisition Number: 267538 Personnel Area: MEDICAL CENTER

Location:

Durham, NC, US, 27710

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.

The Department of Biostatistics and Bioinformatics at Duke University School of Medicine is seeking an Associate in Research to join an interdisciplinary research group developing advanced machine learning and transformer-based models for large-scale biological data. In this role, you will work closely with the Principal Investigator Dr. Wenpin Hou and her research team to develop computational models that analyze single-cell multi-omics and perturbation datasets.

Your work will contribute to cutting-edge projects at the intersection of artificial intelligence, genomics, and biomedical discovery. You will help design and implement machine learning models, maintain computational pipelines, and analyze complex biological datasets using high-performance computing environments. This position offers the opportunity to contribute directly to grant-funded research projects, scientific publications, and new computational tools for the biomedical research community.

Minimum Requirements Master's degree in Computer Science, Statistics, Biostatistics, Bioinformatics, Computational Biology, or a related quantitative field. Strong programming skills. Experience with machine learning frameworks such as PyTorch or Tensor Flow. Experience working with large-scale datasets and computational workflows.

Preferred Qualifications Experience with transformer models or foundation models. Experience analyzing single-cell or other high-dimensional biological datasets. Familiarity with GPU computing and high-performance computing (HPC) environments.

Other Requirements Ability to work collaboratively with researchers across computational and biomedical disciplines. Strong organizational and documentation skills to support reproducible research workflows. This position is hybrid eligible. The employee must reside in a Duke University–approved state.

Key responsibilities include:

Develop and implement transformer-based and deep learning models for large-scale biological datasets. Process, curate, and analyze single-cell and multi-omics datasets, including perturbation data. Maintain and optimize computational pipelines and model training workflows in HPC environments. Collaborate with the PI, postdoctoral fellows, and students to advance research objectives and project milestones. Support reproducible research, including workflow documentation, manuscript preparation, and grant-related deliverables.

Choose Duke The Department of Biostatistics and Bioinformatics at Duke University School of Medicine is a globally recognized leader in biostatistics, data science, and AI-driven biomedical research. Our faculty collaborate widely across Duke's medical and data science communities to develop innovative computational methods that advance precision medicine and biological discovery. By joining our team, you will work on cutting-edge AI and genomics research, collaborate with a diverse group of scientists and trainees, and contribute to impactful projects that translate computational advances…