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in Utah to recruit multiple postdoctoral fellows to apply high throughput methods and machine/deep learning to unlock the full potential of the dark proteome. Responsibilities Scientific vision
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. We are seeking a highly motivated and collaborative postdoctoral fellow with relevant research experience and strong critical-thinking skills; however, outstanding recent PhD or MD/PhD graduates who
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will bring experience in either qualitative or quantitative research methods. On the qualitative side, they should be comfortable assisting with interview case selection, conducting stakeholder
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heavy software development component. The successful candidate will perform research in the application of machine learning (ML) techniques to the finite element method (FEM) in the context of composites
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skills and teamwork required. Gathers, organizes and analyzes data through interviews, literature searches, medical record reviews and related non-lab methods for use in studies, publications and other
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seeking a detail-oriented Postdoc Fellow to join the Traumatic Brain Injury and Concussion Center research team. The preferred condidates in this role will have a PhD in Neuropsychology, Psychology
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. Access to state‑of‑the‑art core facilities and an extensive network of national and international collaborators in vision science. Minimum Qualifications Preferences Ideal candidates will have a PhD or MD
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, education (our Population Health Sciences PhD Program), and community engagement activities, we promote patient-centered health care and the delivery of evidence-based health innovations that improve
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in Zeiss ZenBlue, Nikon Elements, ImageJ/FIJI, and lab-specific ML/statistical platforms to generate quantitative results. 5. Review relevant literature and protocols. document new methods in
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: A PhD in a relevant discipline, such as kinesiology, biomechanics, engineering, or rehabilitation science Additionally, the ideal candidate will possess the following preferred qualities: Expertise in