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learning minimal residual algorithm for PDEs with non-linear quantities of interest. Design and analyze a deep learning minimal residual algorithm guaranteeing uniqueness of the solution for inverse problems
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We invite applications for the position of Postdoctoral Research Associate in Machine Learning/Machine Learning Scientist to join the Deep Medicine programme at the Nuffield Department of Women’s
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that exploit Deep Learning structure prediction methods for the benefit of structural biologists. The work, in collaboration with CCP4 partners and building on preliminary data, will develop software to validate
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that one would like to answer. This position can be a valuable experience for learning more about academia, gaining advanced skills (e.g., computer vision, AI, deep learning, team working, etc.) and can be
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reaction mechanisms remain not fully understood. To address these gaps, we are utilizing AI to autonomously identify chemical reaction mechanisms. Our approach combines deep learning for predicting potential
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(s) extension on related projects. As part of your roles, you will design and develop ML algorithms that make deep learning models learn on the fly and solve multiple tasks efficiently on embedded
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Engineering, Mathematics, or a related discipline (or near completion). Recent relevant research experience in machine learning/deep learning. Strong publication record commensurate with career stage and
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efficiency and environmental sustainability. Your scientific research will focus on the development of machine/deep learning-based medical image analysis methods for computerised tomography scans (CT scans
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research groups relevant to this project The Person Knowledge, Skills and Experience • Expertise in Deep Learning Essential • Strong machine learning delivery skills • Strong software development
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representations. Taking advantages of recent advancements in deep learning, these representations have shown significant improvement in building new knowledge and acquiring new skills for AI agents and practical