651 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in United Kingdom
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Fixed-term: The funds for this post are available for 12 months. Applications are invited for a Research Assistant (RA) to join the Prorok Lab in the Department of Computer Science and Technology
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying
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learning, at the intersection of reinforcement learning, deep learning and computer vision, in order to train effective robotic agents in simulation. You should hold a relevant PhD/DPhil (or near completion
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evaluations, attacks on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related
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Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research Associate: A PhD (or
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following areas: Computer Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with experience in: Deep learning Medical imaging computing
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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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methods suitable for legged systems in physically-realistic simulated environments and on real robots. You should hold or be close to completion of a PhD/DPhil in robotics, computer science, machine