The Department of Radiology at the Perelman School of Medicine at the University of Pennsylvania seeks candidates for an Assistant Professor position in the non-tenure research track. Expertise is required in the specific area of artificial intelligence (AI), computation imaging and analysis, and machine learning. Strong expertise in imaging physics, radiomics, and explainable AI is needed. Applicants must have a Ph.D. or equivalent degree. An equivalent degree in computer science, electrical or computer engineering, or a related field with at least 5 years of postdoctoral research experience is strongly preferred.

Research or scholarship responsibilities may include leading independent and collaborative research projects aimed at AI, radiomics, image computing and analytics to improve screening and diagnosis of diseases, such as breast cancer. Particular strength is sought in multidisciplinary research, emphasizing explainable AI, and physics-informed methods and physics simulations.

Research in identifying factors contributing to cancer disparities is encouraged. Importantly, experience in grant writing and prior success in obtaining grant funding is an asset, as is an established track record of conference and peer-reviewed publications. Candidates should have a proven track record of working in independent and collaborative research settings, and experience in mentoring trainees.

The successful candidate will work in the Physics Section of the Department of Radiology, and collaborate with various laboratories, centers and institutes at Penn, such as the X-ray Physics Lab, the Laboratory for Advanced Computed Tomography Imaging, the Abramson Center, and the Institute for Translational Medicine and Therapeutics.

The University of Pennsylvania is an equal opportunity employer. Candidates are considered for employment without regard to race, color, sex, sexual orientation, religion, creed, national origin (including shared ancestry or ethnic characteristics), citizenship status, age, disability, veteran status or any class protected under applicable federal, state, or local law.