Assistant Professor in Precision Health (Tenure-Track) #FMD012
The University of Chicago

Job Info

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Description

The University of Chicago's Department of Family Medicine (DFM) in the Biological Science Division (BSD) invites applications for a tenure-track faculty member at the rank of Assistant Professor who will join the Institute for Population and Precision Health (IPPH). We seek applicants pursuing research in precision health and related areas.

The appointee will conduct research at the intersection of machine learning (ML)/artificial intelligence (AI), and healthcare. They will develop innovative AI/ML methodologies to address key challenges in population/family health and precision medicine, such as disease prediction, early diagnosis, treatment personalization, and the understanding of complex biological/medical systems. Research areas may include (but are not limited to) epidemiology, clinical studies, gene-environment profiling for new disease diagnostic models, and refined disease risk estimates. Additionally, the appointee may explore machine learning strategies for genomic interpretation, multimodal data integration, and the use of electronic health records to improve patient outcomes. We expect the appointee to thrive in a collaborative environment and actively seek out work with colleagues across the BSD and other Divisions and Schools within the University. The appointee will be expected to teach at the undergraduate and/or graduate level. Compensation (including a generous package of fringe benefits) is dependent upon qualifications.

Prior to the start of employment, qualified applicants must have a doctoral degree or equivalent.

To be considered, those interested must apply through The University of Chicago's Academic Recruitment job board, which uses Interfolio to accept applications: https://apply.interfolio.com/143670. Applicants must upload a CV including bibliography and research statement. Review of applications ends when the position is filled.

For instructions on the Interfolio application process, please visit:http://tiny.cc/InterfolioHelp.

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