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Established in 1930, Duke University School of Medicine is the youngest of the nation’s top medical schools. Ranked tenth among its peers, the School takes pride in being an inclusive community of outstanding learners, investigators, clinicians, and staff where traditional barriers are low, interdisciplinary collaboration is embraced, and great ideas accelerate translation of fundamental scientific discoveries to improve humanhealth locally and around the globe.
Comprised of 2,400 faculty physicians and researchers, the Duke University School of Medicine along with the Duke University School of Nursing and Duke University Health System create Duke Health. Duke Health is a world-class health care network. Founded in 1998 to provide efficient, responsive care, the health system offers a full network of health services and encompasses Duke University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Primary Care, Private Diagnostic Clinic, Duke Home and Hospice, Duke Health and Wellness, and multiple affiliations.
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The project is to develop statistical and computational methods to integrate and analyze large-scale single-cell multi-omics data, primarily data from single-cell RNA-seq/CITE-seq, single-cell immune profiling, single-cell ATAC-seq, and spatial transcriptomics. The project will focus on the integration of data from multiple individuals and multiple modalities. These methods will be applied to COVID-19 research to help understand the immune response differentiating mild and severe COVID-19 patients, as well as extensive collaborative projects studying cancer immunology, transplant immunology, neurological disorders, etc.
The successful candidate will take a leading role in developing the aforementioned methods and applying the methods to single-cell sequencing data from collaborative projects and publicly available databases.
Candidates must have a Ph.D. in Biostatistics, Computer Science, Computational Biology, Statistics, Mathematics/Applied Mathematics, Genetics, or a related field. Required experience: R/Python, Linux, and strong statistical or computational skills. Candidates with experience in single-cell genomics, data integration, immunology, deep learning, and image processing are especially welcomed to apply. The initial term for the appointment is 2 years with the possibility of extensions.
Min Degree Requirements: Ph.D. or equivalent doctorate (e.g. Sc.D., M.D., D.V.M.). Should be used for post-doctoral fellows if the candidate has completed all of the requirements for a degree, but the degree has not been formally conferred; the candidate may present evidence of completion of the degree requirements, together with a statement documenting the date on which the degree is to be conferred.
Other Credential/Experiential Requirements: The incumbent must be a true post-doctoral fellow registered with the Post Doc Office and per the following requirements:
The term of this appointment is limited (5 years with a possible extension for an additional year)
The appointment involves substantially full-time research or scholarship, which may include teaching responsibilities.
The appointment is viewed as preparatory for a full time academic or research career.
The appointment is not part of a clinical research training program, unless research training under the supervision of a senior mentor is a primary purpose of the appointment.
The appointee works under the supervision of a scholar or a department at Duke University.
The appointee has the freedom, and is expected to publish the results of his or her research or scholarship during the period of the appointment.