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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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used to develop networks capable of self-learning and self-optimisation, adapting to real-time changes in traffic and demand. The successful candidate will contribute to designing solutions that optimise
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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
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demonstrated spin-electric excitations through magneto-FIR spectroscopy. To expand the range and depth of these observations, we are looking to develop new molecules and study the effect of synthetic parameters