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Context and Motivation Bilevel optimization problems, in which one optimization problem is nested within another, arise in a wide range of machine learning settings. Typical examples include
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this Ph.D. topic proposal: • The optimal approximation of 3D shapes using meshes is known to be a NP-hard problem. This means that finding the best possible mesh representation for a given shape, while
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surveillance, random testing, wastewater, hospital surveillance) may help optimize epidemic monitoring, iii) modelling and comparing the patterns of spread of COVID-19, influenza and RSV by age group in France
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on optimization) and in general be keen on using mathematics to model real problems and get insights. He should also be knowledgeable on machine learning and have good programming skills. Previous experiences with
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The candidate will optimize an instrumentation and a microfluidic card for encapsulating human cells in monodisperse microbeads of extracellular matrix. Within a few days, cells encapsulated in
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setup, process optimization, and safe, efficient upscaling strategies across various research projects. This position is ideal for someone with a solid understanding of chemistry and polymer science
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suitable data models [CSC+23]. Objectives As far as the design of efficient numerical algorithms in an off-the-grid setting is concerned, the problem is challenging, since the optimization is defined in
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the world and there is an urgent need to have better prognosis and predictive biomarkers, in order to improve the optimal care of these patients. Many existing therapies lead to an improvement of the overal
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theory, as well as the calculus of variations and optimal transport. The ability to participate in the animation of a scientific theme carried by mathematical analysis and to create connections between
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the optimization and development of new protocols and applications; Prior experience with rodent experimentation, with a Function A / FELASA B certification or equivalent; Experience in services-oriented functions