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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
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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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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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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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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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views in real time. Yet raw video and point-cloud streams are massive, wireless links are unreliable, and safety demands that information be both timely and trustworthy. IONIAN tackles this bottleneck
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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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online application system via the above 'Apply' link. Further information can be obtained by emailing Dr Gregor Leckebusch (g.c.leckebusch@bham.ac.uk ) and/ or Louise Harry (louise.harry@siemens.com