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We are seeking a highly motivated postdoctoral researcher with the following qualifications: • PhD in Mathematics, Computer Science, or a related field. • Solid background in optimization and/or
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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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Nature Careers | Port Saint Louis du Rhone, Provence Alpes Cote d Azur | France | about 23 hours ago
research should align with AFMB’s flagship thematic areas: virology and glycobiology. The AFMB Laboratory provides an optimal environment to bridge in silico results with experimental work. Its state
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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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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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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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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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understanding of how neural coding and speech perception are degraded in individuals with Auditory Neuropathy Spectrum Disorders (ANSD) [1]. The project leverages physiologically-informed computational models
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on stochastic Riemannian optimization algorithms, these methods still suffer from limitations in computational complexity. The post-doctoral fellow will build upon this preliminary work to investigate