7 machine-learning-prediction-modelling positions at Chalmers University of Technology
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machine learning and AI for clinical decision support. Develop, train, and validate predictive and explainable models using large-scale clinical registry data. Work closely with clinical collaborators
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, applied mathematics, or a closely related field, awarded no more than three years prior to the application deadline*. Documented research experience in machine learning, AI, or statistical modeling. Proven
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modeling, machine learning, and experimental studies, while offering the opportunity to contribute to open-source libraries and collaborate directly with an innovative startup partner. You will be
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of surface sites makes theoretical understanding difficult. This project will develop and benchmark machine learning models to predict local electronic density of states (DOS) at alloy catalytic sites
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tomography, EPR imaging and spectroscopy) to evaluate performance of electrodes and to map electrolyte chemical composition in micrometer resolution, allowing validation of the model predictions. Validation
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tomography, EPR imaging and spectroscopy) to evaluate performance of electrodes and to map electrolyte chemical composition in micrometer resolution, allowing validation of the model predictions. Validation
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systems. This PhD project, part of a national initiative, aims to use AI to design and optimize thermal interface materials (TIMs). It combines machine learning, materials informatics, and experiments