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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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openness to interdisciplinary collaborations Expertise in some area of computer science such as computational complexity, algorithms, data structures, logic in computer science and AI, semantics, theory
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at the interface of machine learning and computational neuroscience. The candidate will be part of the COATI joint team between INRIA d’Université Côte d’Azur and the I3S Laboratory. Project The candidate should
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Research Engineer in optimization and Design Space Exploration for Next-Generation Computing Systems H/F IN SUMMARY, WHAT DO WE OFFER YOU? We are looking for an Research Engineer in optimization and
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, dynamic and innovative researcher to integrate our community. The ideal candidate will possess deep expertise in the application of cutting edge computational methods to understand the brain mechanisms
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and and experience in computational methods applied to structural biology. A strong publication track record.
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, copyrighted, or biased. By studying brain data recordings and building computational models that mimic real populations of neurons, the project aims to uncover active unlearning: how the brain learns
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minimizing error and maximizing efficiency, is computationally challenging—no known polynomial-time algorithm exists to solve it optimally in all cases. Because of this complexity, researchers typically rely
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p x∈R y∈Rp where F is the outer objective and f is the inner objective. Solving such problems is challenging due to the need to compute gradients through
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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