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foundations of feature learning in neural networks. Engage in the life of the CSD, including participating at the weekly seminars. Present results internally and at international venues; Qualifications PhD in
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instruments and high throughput genomics that informs advanced numerical analysis methods (modeling, statistics, machine learning). Plankton encompasses all organisms roaming with marine currents. Those
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” focusing on the effect of a fluctuating environment on the collective dynamics of self-propelled agents, a numerical part on “reinforcement learning” focusing on optimizing communication between agents in a
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of MIXAP on teaching and learning. We aim for a qualitative and quantitative analysis with questionnaires for teachers and students, focus groups, videos, usage logs, etc. • Provide a list of
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Eligibility criteria PhD in Materials Science, Process Engineering, or a similar field. Required Skills: Proficiency in ceramic and composite material development processes, as well as structural, mechanical
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spoken and written is required The candidat must have a PhD in computer science, machine learning, or computational biology The position is available immediately and will remain open until filled
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Description of the offer : We are opening two positions in the field of “Metallic and Oxide Materials for Orbitronics and Magnonics” at Institut Néel, CNRS, Grenoble The first position (PhD
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results in leading conferences and journals Required Qualifications PhD in one of the following areas (or related fields): Machine learning / deep learning Quantum computing / quantum information Applied
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visualization. Experience with GWAS, Bayesian modelling, and/or machine learning applied to biological data. Strong programming skills (R, Python) and ability to manage large-scale -omics datasets. Good
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Skills/Qualifications Strong background in Operating Systems and Linux development Knowledge of memory management mechanisms and system-level programming Experience with Machine Learning models (design