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live in. Your role To this end, one PhD student will be hired to perform research in the domain of quantum computing applied to optimization problems with possible topics covering: Variational quantum
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model. This work will build on recent studies in low-carbon fleet renewal and optimization under uncertainty, including approaches based on dynamic programming [9], fuel price and demand scenarios [10
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Arts et Métiers Institute of Technology (ENSAM) | Paris 15, le de France | France | about 10 hours ago
Technology is proudly certified as a BCorp® and recognized as a Great Place to Work®. Ph.D. project in a nutshell: The digital transformation of industrial processes relies on sophisticated instrumentation
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learning community. Basically, once the observed data is identified with a probability distribution (possibly the empirical mass function), optimal transport allows to consistently assess the similarity
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., hyperparameter tuning, meta-learning). This project builds upon recent work on stochastic bilevel optimization and variance reduction strategies, such as: • M. Dagr´eou, P. Ablin, S. Vaiter, T. Moreau. A framework
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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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training. #### **Future Directions** - Investigate zero-order optimization and natural gradient combinations. - Extend influence functions to account for optimization algorithms' implicit bias. --- **Key
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of squares hierarchies to prove positivity of holonomic functions - Scientific article writing - Attending conferences - Software programming LAAS CNRS Where to apply Website https://emploi.cnrs.fr/Candidat
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, we will make full use of X‐ray Absorption Spectroscopy (XAS), including X‐ray Magnetic Circular Dichroism (XMCD) - an inherently element- and orbital-selective technique - alongside X‐ray diffraction
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to quantum physics. This project is part of an interdisciplinary research program. The successful candidate will join a collaborative team where bioinformaticians and experimentalists work closely together