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Postdoc Modelling, CFD and Experimental Development of an Innovative Absorption Injector H/F Modelling, CFD and Experimental Development of an Innovative Absorption Injector The Postdoctoral
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Sujet de stage This postdoc aims to enhance PULSE, a generative (VAE) method revolutionizing predictions for disordered materials. You'll improve its accuracy, uncertainty quantification, and transition
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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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well as their integration into the existing process flow. Using an innovative direct etch approach, the postdoc will study the impact of the process step on the superconducting properties. The influence of line dimensions on
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(M2) or engineering-school student in machine learning, applied mathematics or computer science Strong linear algebra; probability and optimization are a plus Solid Python and PyTorch Care in designing
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representative tests in small-scale batteries. A multidisciplinary team is involved in the project with much excellence and expertise in the topic. An example of a recent related research can be found here: https
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develop and apply cryo-ET on microalgae from laboratory cultures and field samples. At LPCV, you will contribute to the research themes of the Photosymbiosis team led by Johan Decelle (https
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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