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: Education: PhD in Biomedical, Neuroengineering, Electronic or Electrical Engineering, Physics, Bioinformatics or related engineering fields · Advanced Python / MATLAB programming skills. · Electrophysiology
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with high temporal and spatial resolution and broad wavelength tunability. Our aim is to gain an increased understanding of the ultrafast microscopic processes related to heat and charge, and exploit
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and astroparticle physics. The members of the group are D. Blas, E. Masso, A. Pomarol, O. Pujolas, M. Quiros, F. Rompineve, E.Salvioni and A. Wulzer. Applicants should have a PhD degree in Physics by
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today. Their convergence has the potential to redefine how we simulate, optimize, and understand complex physical systems. Integrating AI into quantum computers and simulators can help overcome current
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), Claudio Gatti (LNF, Italy), and Matthias Schott (U. Bonn, Germany; leading PI). The successful candidates will join the GravNet-IFAE group, in charge of developing and optimizing all theoretical aspects
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-anticipation Brief Theme Description: Current Foundation Models (FMs) excel at high-dimensional statistical pattern matching, yet they often lack an internal representation of the causal dynamics governing