The Computational Medicine Program, the Lineberger Comprehensive Cancer Center, and the Department of Genetics at the University of North Carolina at Chapel Hill (UNC-CH) invite applicants for a tenure-track faculty position in Computational Medicine and Department of Genetics. The Computational Medicine Program at UNC-CH is an established research initiative that seeks to integrate modern computational approaches, including mathematical modeling, machine learning, computational genomics and network analysis, with cutting-edge experimental techniques, to address problems relevant to human health. While the area of study is flexible, an ideal candidate would apply methods from systems biology and/or genomics to investigate molecular processes dysregulated in cancer or cancer relevant human diseases, and to eventually develop predictive models of these disease states. The successful candidate will be a member of the Computational Medicine Program and The Cancer Center, hold research laboratory space within the Computational Medicine Program, and hold a faculty position within the Department of Genetics. They will be expected to direct an independent research program supported by extramural funding and participate in team science projects initiated through the Computational Medicine Program. The successful candidate will also participate in graduate student mentoring and teaching at the graduate level.

PhD or equivalent degree is required in Genetics, Computational Biology, Computer Science, Statistics, Mathematics or related fields.

The successful candidates will have significant research experience applying computational approaches to problems in biomedical research. While postdoctoral experience is not required, 3-6 years of postdoctoral experience is typical. Current Assistant and Associate professors are also welcome to apply.

Preferred qualifications, competencies, and experience:
Strong training and experience in applying computational and quantitative approaches to problems in cancer-relevant research. It is anticipated that some candidates may be entirely computational, while others will incorporate an experimental component into their research; both types are eligible and encouraged to apply.