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. Delivered in collaboration with Intel, including industrial co-supervision. The student will work with Durham University academic supervisors and an Intel co-supervisor on compact Physical AI, data-efficient
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decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch energy
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, Hospital Clínic, Hospital Sant Pau, Hospital Josep Trueta, Hospital del Mar and Hospital San Joan de Déu. This facilitates close collaboration between basic and clinical researchers, fostering translational
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scientific initiative focused on AI-assisted reverse engineering of integrated circuits for hardware assurance and intelligence analysis. The project is conducted within the Deep Learning for Perception and
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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metabolomics, lipidomics, proteomics and genomics, and combine these data using statistical and machine-learning approaches. Established markers such as neurofilament light chain (NfL) and GFAP will provide a
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pharmacy. In close collaboration with partners from industry, healthcare, and society, we contribute to the urgent challenges of our time, such as energy, sustainability, digitization, and medical technology
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reaction mechanisms. In collaboration with the Chair of Physical Chemistry we will advance CSIA to mechanistically characterize photocatalytic reactions under controlled conditions, with the ultimate goal
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Job description We invite applications for a fully funded PhD position in the area of Scientific Machine Learning (SciML), which integrates data-driven machine learning techniques with established
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(e.g., taxonomy, evolution, ecology, and geology). You will receive dedicated supervision from an experienced researcher and work closely with several international experts and collaborators with whom