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Your profile Candidates should have an exceptional academic record and a robust mathematical foundation. They should have published works at the main conferences in the field of machine learning
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science, chemistry, electrical engineering or a related discipline Strong background in materials informatics and data science Proficiency in Python programming Experience in machine learning for materials
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industrial partner, you will design and implement innovative architectures for real-time detection and control of laser processes. This interdisciplinary role combines artificial intelligence and machine
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, particularly on measurements and searches using jet substructure and development of advanced techniques in particle tagging, including applications using machine learning, and are expected to take leading roles
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utilises cutting-edge recording techniques, including two-photon calcium imaging, high-density Neuropixels electrophysiology, and spatial transcriptomics, alongside computational analyses, to uncover novel
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; collaborating closely with molecular biologists, computational modelers, and clinical and preclinical research partners; documenting results clearly and contributing to publications and presentations; and
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. You will perform microstructural characterization of dry coated electrodes using physical and machine learning based methods and the electrochemical assessment of the electrodes in battery cells. Your
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of academic output. Presenting the project internally and externally, and preparing material for such presentations. Profile Mandatory Requirements: You have: Demonstrable experience with machine learning tools
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University of Basel, Condensed Matter Theory and Quantum Computing Position ID: University of Basel -Condensed Matter Theory and Quantum Computing -POSTDOC [#21540] Position Title: Position Type
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open-source platform redefining how viral sequence data is shared and governed globally, powered by the modular, federated backend database software Loculus This is a computational position focused on