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We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling to apply and develop cutting-edge deep generative probabilistic models
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to the 30th September 2026. We are looking for outstanding machine learning researcher to join the Torr Vision Group and work on AI Scientists: systems that use foundation models, AI agents, and robotics
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collaborative manufacturing and the circular economy. You should possess a Ph.D. in machine learning, robotics or a closely related field with a focus on compositional world models. Further, essential are a
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to work within one of, or across, the four research themes: Learning with Structured & Geometric Models, Low Effective-dimensional Learning Models, Implicit Regularization, and Reinforcement Learning
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* together with relevant experience. You will have a strong technical background in machine learning, especially RL and LLMs. An ability to work independently and as part of a collaborative research team is
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will contribute to the development of a new simulation-based pre-training framework for building more robust and trustworthy machine learning-based clinical prediction models. Funded by the Medical
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the next generation of PV technologies for beyond 2030. The new postdoctoral research position will use materials modelling techniques (DFT, molecular dynamics, machine learning potentials) to investigate
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particular focus on helping build machine learning models that can help humans learn faster and more effectively, and/or make better decisions. They will independently manage their academic and associated
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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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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