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Field
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Qualifications Experience with graph neural networks, machine-learning interatomic potentials, or related scientific machine-learning methods for atomistic systems. Familiarity with uncertainty quantification
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
. 5. Y. Ban, X. Alameda-Pineda, L. Girin, and R. Horaud, "Variational Bayesian inference for audio-visual tracking of multiple speakers," IEEE TPAMI, 2019. 6. X. Alameda-Pineda et al., "Socially
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/instruction tuning methods. * Understanding of Reinforcement Learning (RL) principles, multi-objective optimization, or active learning/Bayesian optimization. * Strong programming capabilities in Python
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groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative projects with other group members and our
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theoretically, in tight collaboration with experimental groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative
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. Experience with uncertainty quantification, Bayesian inference, inverse modelling, parameter estimation, or model calibration. Experience with high-performance computing, surrogate modelling, reduced-order
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/ Deep Learning Knowledge of: Active learning, Bayesian optimization Reinforcement learning or decision-making systems Experience with: Python ecosystem (PyTorch, Scikit-learn) Data pipelines and
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areas will be considered when selecting candidates: Machine Learning, Neural Networks, Numerical solutions of Partial Differential Equations and Stochastic Differential Equations, Numerical Optimization
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transcriptomics. He is the lead developer of widely used open-source software including BayesPrism, a Bayesian deconvolution framework selected as a Nature Cancer 2022 highlight. Dr. Chu's research has been
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motivated researcher to develop a strong independent research profile at the interface of Bayesian statistics, clinical trial design, optimization, computational statistics, and/or translational cancer