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the knowledge acquired during the PhD with team members and acquire new knowledge. - Engage with the Local team at LIPN and the wider national community working on proof theory, programming languages and
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FieldComputer scienceYears of Research Experience1 - 4 Research FieldMathematicsYears of Research Experience1 - 4 Additional Information Eligibility criteria Skills/knowledge: computer vision, neural networks
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Information Eligibility criteria Applicants should hold a PhD in theoretical chemistry, physics, materials science, or a related field; -demonstrate strong expertise in machine learning (regression, neural
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of Research ExperienceNone Research FieldHistory » History of scienceYears of Research ExperienceNone Additional Information Eligibility criteria Education: PhD in Computer Science, Artificial Intelligence
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze
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quantitative and machine learning approaches ● Developing predictive models linking nuclear features to future cell fate ● Interacting with collaborators in imaging, computational biology, and developmental
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Additional Information Eligibility criteria Training and experience: A PhD in Materials Science, Computational Chemistry, Physics, or a related field, with a strong background in DFT modeling and experience in
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for the analysis of hyperspectral imaging data applied to pictorial layers, based on coupling physical radiative transfer models (two-flux and four-flux approaches) with machine learning methods. The researcher will
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of 3D crystalline structures; – depending on the candidate's profile, implementing machine learning methods (AI & machine learning) for the analysis of physicochemical data from the hpmat.org database
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the impact of collective effects in high space-charge regimes. The Accelerators and Ion Sources Pole of LPSC is involved in the design, construction, and operation of the PERLE machine, particularly in