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statistical and mechanistic mathematical modeling, causal inference, and machine learning, applied to longitudinal multi-omics data from pediatric cohorts spanning diverse socio-economic and geographical
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of translating our insights into actionable strategies for pediatric care. Our work combines statistical and mechanistic mathematical modeling, causal inference, and machine learning, applied to longitudinal multi
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insights into actionable strategies for pediatric care. Our work combines statistical and mechanistic mathematical modeling, causal inference, and machine learning, applied to longitudinal multi-omics data
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, and machine learning, applied to longitudinal multi-omics data from pediatric cohorts spanning diverse socio-economic and geographical contexts. Our lab will be supported by two major grants starting in
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référence. Les candidatures sont à déposer au format PDF via la plateforme de recrutement de l’Idiap : https://careers.werecruit.io/fr/idiap . Délai de postulation : 12 octobre 2026 Role Summary As Deputy
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Teaching the module M05 Computer Vision & Perception. Developing and delivering module content suitable for online teaching. Providing online resources and learning material for our teaching platform
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required; the project-specific methods and concepts can be learned during the doctoral studies. You are fluent in English (oral and written). You enjoy working in a team, possess the necessary social skills
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and Communication Sciences, are strongly encouraged. The candidate's ability to teach STEM subjects and/or bioengineering topics will be a key selection criterion. EPFL offers world-class research
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the field of the Mathematical Foundations of AI for Science and Engineering (also known as Scientific Machine Learning). The new professor will lead an internationally high-profile research and teaching
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of computational and applied mathematics, including but not limited to data-driven numerical modeling, scientific machine learning and AI for science and engineering, computational uncertainty quantification