671 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in United Kingdom
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PhD/DPhil in Computer Vision or Machine Learning (or be near completion) and hold a strong publication record in this field. You must have sufficient theoretical and practical knowledge of methodologies
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implementation of deep learning and computer vision frameworks across a range of research projects. This includes developing and training deep learning models for tasks such as scene understanding, object
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The Role The successful applicant will be responsible for the design, development, and implementation of deep learning and computer vision frameworks across a range of research projects
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We are seeking a full-time Postdoctoral Research Associate in Machine Learning for Grid-Edge Flexibility to join the Power Systems Architecture Lab within the Department of Engineering Science
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be considered. You should possess a PhD or DPhil (or near completion of) in Computer Vision or Machine Learning. You should have knowledge of approaches for areas related to efficient, reliable, and
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optimization, machine learning, and distributed algorithms. Candidates should have expertise in mathematical optimization, statistical learning, or decentralized computation, with a demonstrated ability to
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) at Northeastern University London (NUL) is looking for an exceptional candidate to fill an open Postdoctoral Research Associate position in Network Science, Graph Machine Learning, and Cognitive & Social Sciences
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We are seeking a full-time Postdoctoral Research Assistant in Machine Learning and Power Systems to join the Energy and Power Group at the Department of Engineering Science (Osney). The post is
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We are seeking a full time Postdoctoral Research Assistant in Safe Machine Learning for Power Systems to join the Foerester Lab for AI Research (FLAIR) at the Department of Engineering Science
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machine learning applications. In this role, you will play a vital part in optimising respiratory drug delivery for diseases such as COPD and asthma. Working within a dynamic, multidisciplinary team, you