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controlled via structural phase transitions or external fields. The successful candidate will develop and apply a range of theoretical and computational methods based on first-principles electronic structure
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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SPINTEC fabrication facilities. As such, this thesis will be stationed mostly at SPINTEC in Grenoble, the PhD program being registered at Université Grenoble Alpes. You will also be part of the Vertical
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! Education Master's degree (Bac+5) in telecommunications, computer science, or a related field, with an interest in AI, cognitive networks, or connected vehicles. Experience and skills Prior experience with
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be expected to teach advanced courses in Artificial Intelligence—particularly in machine learning, statistical learning, natural language processing (NLP), symbolic AI, computer vision, and related
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The Machine Learning for Integrative Genomics team at Institut Pasteur, headed by Laura Cantini, works at the interface of machine learning and biology, developing innovative machine learning
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study and other ongoing translational initiatives to develop a voice-based digital health solution to alleviate the diabetes burden. Project objective The PhD candidate will work at the interface
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Background Cardiovascular disease (CVD) remains the leading cause of death worldwide and exerts a disproportionate burden on individuals living with type 1 diabetes (T1D). Despite advances in care, traditional risk prediction models like the Steno Type 1 Risk Engine fail to account for the...
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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functional readouts to score these properties. Skeletal muscles in the head and trunk actually follow distinct developmental trajectories, a perspective our work has significantly advanced (4) . In particular