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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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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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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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electromagnetic signatures, primarily focussed on linking the data from these exciting experiments with our theoretical understanding of gravity and the most extreme regions of the Universe. I am a member of the
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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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twins, energy islands, electrolyzers, and machine learning. Our team of 25 members (link ) from 13 different nationalities values diversity and includes experts in a broad range of scientific disciplines
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available, tailored to the needs and aspirations of the successful applicant. More information on the academic supervisor and EDC collaborations with JLR is available here: https://www-edc.eng.cam.ac.uk
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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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Enrolment The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment