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, with the longer-term objective of improving the prediction of fast-charging behaviour. Your project will be to build or adapt a machine-learning interatomic potential for lithiated graphite using density
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their 4th or 5th year of studies (M1, M2 or gap year) - Computer vision skills - Machine learning skills (deep learning, perception models, generative AI…) - Python proficiency in a deep learning framework
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different dyadic motor coordination tasks. A range of neurophysiological measures (EEG, ECG and fNIRS) as well as behavioural measures will be recorded simultaneously from both partners. Machine-learning
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in privacy preserving machine learning (ML) within the SSF-ML-DH project, under the supervision of Olivier Cappé (CNRS, DI ENS) and Jamal Atif (Ecole Polytechnique, CMAP). Funding is available for two
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programming skills. Skills in machine learning, knowledge representation and big data analysis are expected. Skills in statistical modelling, optimisation or symbolic reasoning will be an asset. The desired
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, integrating statistical inference, machine learning, and population genetics. We will develop advanced computational methods to characterize the functioning of T- and B-cell repertoires. The goal is to build
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Eligibility criteria - Education: Ph.D. degree in Robotics, Control, Optimization, Machine Learning, Computer Vision for Robotics, or related fields. - Technical Expertise: Strong background in optimization
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., Reinforcement Learning in Different Phases of Quantum Control, Phys. Rev. X 8, 031086 (2018). [8] J. Biamonte et al., Quantum Machine Learning, Nature 549, 195 (2017). [9] E. Célanie, L. Delisle, and A. Jaouadi
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
learning, privacy, security and distributed systems. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2026-10411 Requirements Skills/Qualifications We are looking for a candidate with
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 2 months ago
machine learning, explainable machine learning, fairness and data protection legislation. Privacy-preserving machine learning aims at learning (and publishing or applying) a model from data while the data