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Field
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models when faced with data drift, bias, and fairness challenges. The research will involve developing deep learning and synthetic data generation approaches and applying them to exemplar studies in
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) a PhD in a quantitative discipline such as computer science, mathematics, statistics, engineering, or a related field. Strong programming skills and experience in machine learning or statistical
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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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of Information Technology, and will be conducted alongside other researchers at the Centre for image Analysis who develop computational methods with a particularfocus on deep learning and image analysis. The project relies
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the Oxford–Novartis Collaboration for AI in Medicine. You must hold a PhD/DPhil in Statistics, Statistical Machine Learning, Deep Generative Modelling, or a closely related field, together with relevant
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laser processing and to bring your ideas in AI/ML to the technology level. You have a solid background in programming (deep learning, reinforcement learning, etc.), electronics, high-speed data
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researcher with: A PhD in machine learning, computer vision, remote sensing, glaciology, climate science, or a related field Strong programming skills (Python) and experience with deep learning frameworks (e.g
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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breakthroughs in deep learning–powered protein design, recognized by the 2024 Nobel Prize in Chemistry, have enabled the creation of proteins with near-atomic accuracy. Models such as RFdiffusion, LigandMPNN, and
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At the Technical Faculty of IT and Design, Department of Sustainability and Planning (PLAN), a Postdoc position in Satellite Data Processing and Machine/Deep Learning is open for appointment from