Postdoctoral Researcher – Machine Learning and Computational Pathology

Monday 13th June 2022

Organization Scientific Computing and Imaging Institue, University of Utah
Location Salt Lake City, Utah, USA
Title Postdoctoral Researcher – Machine Learning and Computational Pathology
URL https://utah.peopleadmin.com/postings/134708
Email Address shireen@sci.utah.edu
Description The Scientific Computing and Imaging (SCI) Institute at the University of Utah invites applications for one or more full-time (1.0 FTE) post-doctoral researchers for interdisciplinary work that involves the analysis of medical images from pathology slides. The SCI Institute is seeking highly talented and committed individuals with a demonstrated ability to work well with minimal supervision in a multi-disciplinary research environment. Successful candidates will enjoy being part of a world-renowned research institute and working closely with graduate students, post-doctoral researchers, software developers/engineers, research scientists, and faculty members to develop cutting-edge computational and mathematical tools.

Successful candidates will contribute to the Institute's world-class research and software development in biomedical image analysis. They will perform research at the interface of machine learning, image analysis, and computational pathology, and work closely with SCI Institute researchers and collaborators in the Department of Pathology. The long-term goal of this interdisciplinary research is to develop algorithms that lead to more precise and cost-effective responses to cancer treatments and to better patient care.

Please contact Profs. Ross Whitaker (whitaker@sci.utah.edu) and/or Shireen Elhabian (shireen@sci.utah.edu) for further information.

Salary Range: $58,000 - $78,000 based on qualifications, training, and experience.

Start Date and Term: Start date is immediate, preferably before August 1st, 2022. The initial appointment will be for a 2-year period, with the possibility of an extension based upon performance and availability of funding.