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progression. This project addresses the challenge of studying early tumorigenesis in pancreatic cancer by developing advanced in vitro models based on human extracellular matrix (ECM), aiming to recreate
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stacking, both high performance and (very) high density can be achieved by this concept. The mission will be to explore, understand and develop the fundamental physics of device operation. This will require
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, France) and at the ESRF ID12 beamline (Grenoble, France), under the co-supervision of Prof. Olivier Isnard (Néel Institute) and Dr. Fabrice Wilhelm (ESRF). This PhD project is co-funded by University
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slicing. - Develop advanced AI/ML algorithms and data analytics techniques to automate and optimise exposure requests, adapted to available resources and real-time demand. - Propose and
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Wikibase instance Curate and model historical migration datasets within the dedicated Wikibase instance Contribute to the design of ontologies and metadata schemas for the knowledge graph Develop data-driven
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contribute to the development of the Institute’s academic programs, mainly aimed at master's students, but also for bachelor's degrees, on-the-job training and MOOCs. The applicant will participate in
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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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within the Faculty. Along with the disciplinary approach a very ambitious interdisciplinary research culture has been developed. The faculty's research and teaching focuses on social, economic, political
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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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and epidemiological characterisation of cardiovascular risk among people living with T1D, using multimodal data in the large SFDT1 cohort study. This work will lay the groundwork for developing novel