27 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at New York University
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Details Posted: 31-Mar-25 Location: New York, NY Categories: Academic/Faculty Internal Number: 165609 The Urban Systems Lab is seeking a Postdoctoral Associate in Machine Learning to develop and
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improve our interactions with wild animals at scale. To learn more about the Wild Animal Welfare Program, visit: https://sites.google.com/nyu.edu/wildanimalwelfare Responsibilities The selected candidate
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-reviewed publications. Prior experience with biological network analysis and practical application of a variety of machine learning and computer vision techniques is preferred. The successful candidate will
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record of peer-reviewed publications. A background is required in computer programming (including Julia and/or C/C++), applied mathematics and statistics. Please upload your application materials via
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Postdoctoral Associate to investigate the neural mechanisms underlying continual learning in humans. The successful candidate will develop computational models examining the tradeoff between task
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should have a PhD in Computer Science, engineering or related fields; Applicants should submit a cover letter, a current CV and a list of three references with complete contact information. All application
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to conduct fundamental research in the broad areas of virtual and /augmented reality (VR/AR), computer graphics/vision, generative AI, and neural rendering. Candidates will be making contributions to one
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within any of the relevant disciplines of the humanities, social sciences, and computer sciences are welcome to apply. The ideal candidate is a postdoctoral scholar seeking to examine and develop research
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seeks to recruit a Postdoctoral Associate to work in the field of geotechnical engineering. Required Qualifications: The ideal candidate will hold a PhD in Geotechnical Engineering, Civil Engineering, or
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grant when extending an offer. Completion of PhD in Data Science, Computer Science, Mathematics, or other discipline aligned with CDS faculty research by the start date. Please follow instructions in