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Virtual laboratory to predict the ability of a fluctuating biomass to satisfy a material use-VARIOUS
, the research will ideally be at the crossroads between computational mechanics of solids and materials science (physics, chemistry). Experience with interdisciplinarity would be desirable to ensure the success
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the first Réseau de Compétences Maladies Neurodégénératives/ParkinsonNet (RdC-MN) funded by by the Ministry of Health and Social Security. The “Programme for Dementia Prevention ” (pdp) is a first nation-wide
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the attractivity of doctoral training will be important elements of the selection process. The recruited person is expected to invest in particular in terms of international visibility, project management and
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. • Strong organizational skills, project management capabilities, and team spirit. • Flexibility and proactivity in a startup environment. Education • PhD (preferred) in physics, materials science
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/2023.12.26.573306 (2023). Lake, B. M., Salakhutdinov, R. & Tenenbaum, J. B. Human-level concept learning through probabilistic program induction. Science 350, 1332–1338 (2015). The successful intern should have a
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, or electrophysiology recordings) identified in step 1.2. TheVirtualBrain framework [12] will assist in effectively managing the integration process. Aim 2: Model the computational de-association of memory traces 2.1
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master’s degree in mathematics, physics or informatics with a strong knowledge in machine learning. Skills: Coding in Python and/or R is required. Previous knowledge in archaeology and zoo-archaeology would
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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anticipate risks by integrating all human, technical, and organizational factors into a dynamic model of the OR. This project will be developed within the ICARE team (Artificial Intelligence, Computer Science
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for process-local loose coupling in high-performance simulation codes. PDI supports the modularization of codes by inter-mediating data exchange between the main simulation code and independent modules (plugins