Assistant or Associate Professor of Machine Learning (228054)

The Department of Biostatistics & Medical Informatics, a vibrant and collaborative basic science department in the School of Medicine & Public Health at the University of Wisconsin-Madison seeks applicants for a tenure-track assistant or associate professor whose research focuses on machine learning. The successful applicant for this position will deepen our campus’ interdisciplinary research strength in machine learning, its applications for healthcare and biomedical sciences, and will embrace diversity in the broadest sense. We require a doctorate (PhD or equivalent) in Computer Science, Statistics, Biomedical Informatics, Electrical Engineering, or a closely related quantitative field. Assistant professor candidates must have at least 3 years of relevant research experience, which may have been acquired in the doctoral program. Associate professor candidates must have relevant tenure-track faculty experience. We require a strong methodological research program in machine learning; a demonstrated commitment to interdisciplinary research in basic, translational, or clinical research; and the potential to thrive in our dynamic research environment. We are looking for someone to develop new machine learning approaches, algorithms, and strategies to create more effective predictive models from growing data resources. You will have the opportunity to use electronic health record, genomic, imaging, and other relevant data sources, all of which may inform prediction for clinical outcomes or treatment strategies, as well as data on molecular structures that might guide predictions of protein binding or other molecular characteristics. This is a great opportunity for those interested in machine learning and its application to questions of human health and biomedical science.

The assured consideration date for this position is December 31, 2020, although late applications may be considered. We strongly encourage women and underrepresented minority candidates to apply.

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