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Machine learning skills (deep learning, perception models, generative AI…) Python proficiency in a deep learning framework (especially PyTorch or TensorFlow) Strong interest for 3D
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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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in the field of operational research and/or machine learning algorithms would be a plus. In accordance with the commitments made by the CEA to promote the integration of disabled people, this job is
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to the different model’s parameters. The student will be able to learn an advanced calibration strategy that can be applied to any complex 3D FEM model, potentially involving several multiphysics and non-linear
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to strengthen your skills, acquire new ones, and enhance your mission. A work-life balance recognized by our team members. Remote work options to reduce commuting time and improve your quality of life. A rich
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The detection of out-of-distribution (OoD) samples is crucial for deploying deep learning (DL) models in real-world scenarios. OoD samples pose a challenge to DL models as they are not represented