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and interest. References may be contacted for the candidates who make the shortlist for this position. Applicants must apply online via.: https://puwebp.princeton.edu/AcadHire/position/40241. The review
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. · Strong background in machine learning/AI and hands-on experience with large, heterogeneous datasets. · Practical experience with computer vision and/or spatio-temporal modeling (object detection
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SPECIFICS Postdoctoral Scholar of Machine Learning and Statistical Genomics Description: The Department of Public Health Sciences at the Penn State College of Medicine in Hershey, Pa is seeking postdoc
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. The position is in the Department of Family and Consumer Studies (https://www.fcs.utah.edu ) at the University of Utah. The University is a Big-12, Carnegie RU/VH Research University, a member of the Association
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capabilities necessary to communicate with other researchers and staff in person, on the telephone and by e-mail. Vision capable of viewing gauges, computer monitors, charts, forms, text and numbers
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Movement Sciences at Rutgers University is seeking a highly motivated Post Doctoral Associate to work on translational projects at the intersection of biomechanics, machine learning, exergaming, and mobile
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
articulated in the School’s Strategic Plan (https://pharmacy.unc.edu/about/oe/strategic-plan/). Our Vision is to be the global leader in pharmacy and pharmaceutical sciences. Our Mission is to prepare leaders
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to organize through the Center; and (5) the names of 3 referees. Applications should be submitted online at: https://indiana.peopleadmin.com/postings/29777 . Cover letters should be addressed to: Professors
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. For consideration, please click the link below to apply and submit all required application materials (see list below): https://academicjobsonline.org/ajo/jobs/31185 ">https://academicjobsonline.org/ajo/jobs/31185
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and patient-reported outcomes; (b) observational research and comparative effectiveness studies; (c) intervention studies; (d) clinical informatics, mobile/electronic health; (e) machine learning