79 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Rutgers University
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written communication skills. Must be computer literate with proficiency and working knowledge of database and reporting tools such as Microsoft Word, Excel, and PowerPoint. Background in biochemistry, cell
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mechanics and analysis Experience with the following: Structural health monitoring (SHM) Finite element modeling (e.g., ABAQUS, SAP2000, ANSYS) Machine learning / AI (Python, TensorFlow, PyTorch) Demonstrated
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experiential learning courses, as well as contributing lectures to core plant pathology courses that support required and elective curricula in the Undergraduate Program in Plant Science and Graduate Program in
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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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Docs - Regular Salaried Payroll Designation PeopleSoft Seniority Unit Terms of Appointment Staff - 12 month Position Pension Eligibility ABP Qualifications Minimum Education and Experience PhD degree in
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, computer vision and machine learning algorithms. · Information dissemination and decision-support services · Policy related analysis and investigation · Previous interactions with transportation funding
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fellowship focused on real world evidence, health economics, patient outcomes, market access and policy research. The program provides interdisciplinary training through hands on industry research, academic
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Number 26FA0075 Posting Open Date Posting Close Date 06/30/2026 Qualifications Minimum Education and Experience The successful applicant should have completed a PhD in urban planning, civil engineering
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discipline expertise and computational areas, such as data science, artificial intelligence (AI), machine learning (ML), generative AI and other technology innovations. Key details of this position include
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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