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Electronique embarquée de conditionnement pour électrode de référence dans un accumulateur Li-ion Postdoctoral position in analog embedded electronics and electrochemistry, for Reference Electrode
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dissociation mechanisms, which we will describe using active learning methods to create force fields for which sufficiently long simulations allow access to reaction pathways and their thermodynamic data
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in Artificial Intelligence (Machine Learning and Statistics) at CentraleSupélec, · Joël Eymery, Head of the Nanostructures and Synchrotron Radiation Team at CEA Grenoble, · Jean-Sébastien
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be the continuation of previous work, would use machine learning on a simulated data base to define the tool, followed by an application to real data from GRAVITY/VLTI (K band), MATISSE/VLTI (L, M, N
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biological signals. The project will focus mainly on developing innovative models for biomedical signals with irregular cyclicity and exploring potential machine learning applications. Position Objective
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machine learning applications. Position Objective : The primary focus of this position is to develop concentration inequalities in the nonstationary setting, specifically for periodic Markov chains and
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-criteria, defining their formalization as fuzzy subsets, and characterizing their uncertainty; Integrating Machine Learning algorithms to better account for low-level sensor data (precipitation, wind-driven
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Complexity; Quantum Information and Quantum Learning. The successful candidate will work closely with Augustin Vanrietvelde and his team on the topics of quantum foundations, quantum reference frames and
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the University of Poitiers as well as collaborators in France and abroad. The post-doc will have the possibility to interact and learn from scientists from these diverse backgrounds. We are looking for motivated
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Description Conduct a part of the ANR MetaTime (setting-up experiments, acquisition and processing of data, writing scientific reports) • Perform a review of the existing litterature on the topics • Acquire