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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 20 days ago
making problem under uncertainty. Most of our activities are related to either bandit problems, or reinforcement learning problems. Through collaborations, we are working on their application in various
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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methodology for steel fibre reinforced concrete structures assisted by nonlinear finite element analysis and artificial intelligence tools”, project number 16782, code operation COMPETE2030-FEDER-00796500
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The candidate should have experience in the following two areas: 1) non-destructive testing/evaluation and structure health monitoring, primarily reinforced concrete structures, using mechanical, acoustic
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The aim of this postdoctoral position is to mimic and understand the origin
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview
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dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview
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Statistics and Data Science Center at the Institute for Data, Systems, and Society is seeking applicants for a Postdoctoral Associate in the general areas of statistical learning, reinforcement learning
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patient flow, care pathways, and population-level outcomes • Creating data-driven and privacy-aware decision-support tools for clinicians, administrators, or patients • Integrating multi-source, high