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  • Associate Professor - Tenure - Artificial Intelligence (AI) and Machine Learning (ML) applications to Epilepsy and Traumatic Brain Injury


Associate Professor - Tenure - Artificial Intelligence (AI) and Machine Learning (ML) applications to Epilepsy and Traumatic Brain Injury

2024-02-21 10:22 AM | NNS Office (Administrator)


The Department of Neurology at the Perelman School of Medicine at the University of Pennsylvania seeks candidates for an Associate Professor position in the tenure track. Expertise is required in the specific area of Artificial Intelligence and Machine Learning, particularly as it applies to biomedical signal processing (such as electroencephalography) and imaging analysis, including quantitative tools to analyze magnetic resonance imaging of humans with neurological disorders. Applicants must have a Ph.D. degree.

Teaching responsibilities may include teaching graduate students, residents, and post-doctoral fellows in topics pertaining to Artificial Intelligence (AI), Machine Learning (ML) as it applies to the analysis of multidimensional data relevant to human disease. This will take place in formal didactic lectures, as well as supervising doctoral students and fellows.

Research or scholarship responsibilities may include developing an independent research program related to AI/ML, with a focus on neuroimaging. It is expected that this research will be supported by extramural research grants, primarily from NIH and the Department of Defense. These research activities will include supervision of postdoctoral fellows, students, and research staff. Additionally, the successful candidate will coordinate collaborative research projects with local, national, and international collaborators, and participation in writing grants, reports, and manuscripts.

To apply, visit apply.interfolio.com/138985

We seek candidates who embrace and reflect diversity in the broadest sense. The University of Pennsylvania is an EOE. Minorities/women/individuals with disabilities/protected veterans are encouraged to apply.


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