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) properties and the digestibility (rate and extend of bioavailability). The results will be used for data driven machine learning, in collaboration with other partners in the project. Who are we looking for? We
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) the following documents: A cover letter outlining research interests and goals Curriculum vitae with a detailed list of research skills relevant to the position Contact information for three referees Department
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of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts are supported by
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Continuum mechanics Large deformation elasticity Design of mechanical devices Programming skills As a formal qualification, you must hold a PhD degree (or equivalent). We offer DTU is a leading technical
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and reduction of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts
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Artificial Intelligence (AI), particularly in the development and application of Large Language Models (LLMs), to join our team working on predictive maintenance solutions. The ideal candidate will have
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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, including but not limited to cancer, metabolic disorders, and infections. The research design involves the integration of large-scale biological datasets derived from both the host and the microbiome
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of science to applied technological research and partnership with industry. Your Tasks, Core Themes Candidates will have the opportunity to pursue one or more of the following core themes: 1. Large Pre-Trained
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interpretation of atmospheric circulation in high-resolution reanalysis data, idealised model simulations and a state-of-the-art weather forecasting system. The post-holder will have the opportunity to teach