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Post-doctoral Position in AI Causal models for Synchrotron Anomaly Detection H/F This post-doctoral position is part of a collaboration between LIAD (Laboratory of Artificial Intelligence and Data
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, for a given attacker model, of a system embedding hardware/software countermeasures against fault injections. Gobally, these tools implement a methodology that have shown to be successful to find
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exploration strategies that go beyond traditional techniques such as linear programming or deterministic solvers. You will work on cutting-edge methods including: Bayesian optimization Surrogate modeling
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at Attolab in CEA-Saclay and to advance understanding of the experimental data through modeling. Contract duration (months) 1 year, renewable for 1 additional year Job description Your mission will focus
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genes each with 300 to 3k base pairs. To interpret experimental results, it is necessary to simulate several million experiments for each gene with a model having about ten free parameters (>100Mh with
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progression. This project addresses the challenge of studying early tumorigenesis in pancreatic cancer by developing advanced in vitro models based on human extracellular matrix (ECM), aiming to recreate
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properties and electrical characterization will be carried out. The results will be compared with ab initio calculations and will provide input for physical models based on real devices to predict key metrics