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subteam including supervision of PhD student(s) and will work in close collaboration with experts at Edinburg University, Imperial, Manchester University and other partners in computational biology, genome
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Society for the History of Technology: Brooke Hindle Postdoctoral Fellowship Eligibility: Applicants must hold a doctorate in the history of technology or a related field. The doctorate can be
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(D^3) Institute and the LISH/Data Science & AI Operations Lab seek enthusiastic Postdoctoral Fellows skilled in computer science, statistics, operations research, or related computational fields. As
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Department of Computing Research Fellow / Research Associate (Full-time/Part-time) / Research Assistant (Full-time/Part-time) (Ref. 260312012) (1) Research Fellow (two posts) [Appointment period
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 1 month ago
Preferred Experience, Skills, Training/Education: 1. Ph.D. in Industrial Engineering, Biomedical Engineering, Data Science, Computer Science, or related fields. 2. The candidate is expected to have a strong
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students enrolled in the Master of Science in Blockchain programme, particularly those undertaking six-month capstone projects. Contribute to teaching, tutorials, or guest lectures in courses relevant
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Department of Electrical and Electronic Engineering Senior Research Fellow / Senior Project Fellow / Postdoctoral Fellow / Research Associate / Project Associate / Research Assistant / Project
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Full Time, Fixed term for 3 years This role will be recruited to either a Senior Research Fellow or Research Fellow depending on the pool of applicants we receive. Please clearly indicate in your application which role you are applying for. Please note this is a Laboratory based post and as such...
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The Computer Vision-Core Artificial Intelligence Research (Vision-CAIR ) group led by Prof. Mohamed Elhoseiny at the CS Program of the King Abdullah University of Science and Technology (KAUST) is
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& multidisciplinary research programme focusing on evidence generation to further methodology research and to enable the design & development of in-vitro diagnostics and medical devices for patients and the NHS. NIHR