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programme aims to advance fundamental understanding of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key
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within the ANITI HUCAD project which aims to develop Artificial Intelligence (AI) systems fostering human-machine collaboration for effective deliberations. It aims to enhance the argumentation
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of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key goals include optimising convective heat transfer
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being responsible for the confocal microscope (maintenance). Resources provided (equipment, IT, etc.): office equipped with a computer workstation, equipped laboratory bench, reagents and equipment shared
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on food craving and health-related decision-making. To this purpose, we will use a combination of brain imaging, behavioral measures, and machine-learning techniques. Activities The successful candidate