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Postdoctoral Fellowship: Computational Vision and Medical Imaging

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Position description

The Vision & Image Understanding Laboratory (Eckstein lab) in the Department of Psychological and Brain Sciences at the University of California, Santa Barbara & the Institute for Collaborative Biotechnologies (ICB, http://www.icb.ucsb.edu/) invites applications for a position as a post-doctoral researcher in computational modelling of perceptual decisions with medical imaging.

Requirements: The successful candidate should have a strong technical background and a Ph.D. in any of the following: Electrical Engineering, Computer Science, Medical Physics/Imaging, Mathematics, or related fields. Training and experience with computer vision, pattern recognition, machine learning, computational modeling, and/or model observers for medical imaging.
The position is anticipated to begin August 10, 2015, will initially run for 1 year, and is renewable depending upon job performance and availability of funds. Review of applicants is underway and will continue until the position is filled. To apply, please submit a CV and a statement of research interests. Review of applicant credentials will commence on July 13, 2015 and continue until the position is filled. The department is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching and service. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic by law.

Application Requirements

Document requirements
  • Curriculum Vitae - Your most recently updated C.V.

  • Cover Letter (Optional)

  • Statement of Research

  • Statement of Teaching (Optional)

  • Statement of Contributions to Diversity - Statement addressing past and/or potential contributions to diversity through research, teaching, and/or service.
    (Optional)

  • Misc / Additional (Optional)