Postdoctoral Researcher – Machine Learning and Image Analysis

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 Image Analysis
URL https://utah.peopleadmin.com/postings/134696
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 to engage in the research, design, and deployment of machine learning and statistical methods to solve image analysis problems driven from applications in medicine, science, and engineering. The SCI Institute is seeking a 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 work as part of collaborative, multidisciplinary teams that entail SCI Institute researchers and external collaborators in multiple application domains. They will contribute to establishing theoretical foundations, innovating computational methods, developing robust software packages for inverse problems in image analysis, and applying these methods in several application domains.

Please contact Prof. 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.

OrganizationScientific Computing and Imaging Institue, University of UtahLocationSalt Lake City, Utah, USATitlePostdoctoral Researcher – Machine Learning and Image AnalysisURLhttps://utah.peopleadmin.com/postings/134696Email Addressshireen@sci.utah.eduDescriptionThe 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 to engage in the research, design, and deployment of machine learning and statistical methods to solve image analysis problems driven from applications in medicine, science, and engineering. The SCI Institute is seeking a 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 work as part of collaborative, multidisciplinary teams that entail SCI Institute researchers and external collaborators in multiple application domains. They will contribute to establishing theoretical foundations, innovating computational methods, developing robust software packages for inverse problems in image analysis, and applying these methods in several application domains.
Please contact Prof. 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.