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Job Description Are you passionate about scientific machine learning, particularly physics-informed machine learning? If so, this position might be perfect for you. We are seeking a data scientist
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and materials engineering. For more information about the APE group please use the following link: www.rug.nl/research/ape. The project cooperates with the Bernoulli Institute of Mathematics
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identifying relevant treatments and their associated Health Resource Group (HRG) codes to link hospital care provided with NHS Reference Costs, as well as linking any primary care activity with Unit Costs of
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, the supervision team have obtained data access to indoor environment sensor data at national scale from a leading industrial collaborator. To pair with this big dataset, outdoor environment data at MetOffice can be
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group specializes in experimental quantum technologies spanning quantum information processing, quantum communication, and precision sensing. In this PhD project, you will work at the forefront of solid
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explored using scientific machine leaning. Machine learning, programming experience and a curious mind-set You are fascinated by how computers can learn from data and you have a strong interest in the
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for the efficient formation of high-value compounds. Advanced NMR methods and computational data analysis will be compounded to devise novel reactions towards pharmaceutical precursors, polymer building blocks and
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information, please visit Working at Utrecht University external link . About us A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching
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data integration, cancer systems biology, and single-cell analysis, with strong links to clinical and translational oncology. Our work is based in the dynamic research environment of Heidelberg
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process