183 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at University of Oxford
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in real time. It requires the application of advanced computational techniques spanning a range of temporal and spatial scales to address some important and fundamental questions regarding the nature
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We are seeking a full-time Postdoctoral Research Associate in Computational Mechanics for Solid State Batteries. The post holder will be based at the Department of Engineering Science (central
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capabilities o Demonstrated experience with machine learning and/or statistical modeling o Expertise in handling large-scale, complex datasets with strong data wrangling skills o Strong publication record
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collaborative links thorough our collaborative network. The researcher should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely related field. You have an
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Computational Neuroscience and related fields as part of the Medical Research Council, UKRI grant “Algebraic topology bridging the gap between single neurons and networks”. They will be expected to conduct
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becomes essential. This project will focus on building a comprehensive digital twin of a future quantum computer to investigate how classical subsystems scale and interact, and how this scaling impacts
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conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics, computer science, statistics, or a related field together with strong programming skills in Python, R
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. About the Role The post is funded for 3 years and is based in the Big Data Institute, Old Road Campus. You will join an interdisciplinary team of researchers spanning imaging science, machine learning
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Lives with Linear Accelerators) project, which aims to leverage technologies developed for particle physics, computer vision and robotics into a novel end-to-end radiotherapy system as an essential
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute