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web and linking source populations to the underlying halo and galaxy distribution; developing SBI pipelines for Fermi-LAT data, first standalone and then jointly with LSS. Qualifications. A PhD in
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Eligibility criteria Selection will be based on the following scientific and technical criteria: • PhD in computational biology, machine learning, bioinformatics or a related field. • Proficiency with Python
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used by a PhD student, likely starting October 2027, to initiate development of a deep-learning architecture. The refined batch of synthetic data will be used by the PhD student to finalise the deep
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missions operated by LATMOS. The postdoc will employ deep learning approaches using satellite data and ground stations. -Understanding the infrared data from the IASI mission and identifying the channels
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. Unsupervised machine learning approaches will be used to identifiy key dimensions of circadian rhythm associated with dementia subtypes. This requires a very good level in statistics and R programing as
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oxides, we will first develop and benchmark machine-learning interaction potentials of increasing complexity. Subsequently, we will deploy a combination of brute-force and rare-event sampling to isolate
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of reports with respect to deadlines, scientific publications and patent proposals - Presenting the results internally and externally Profil du candidat Candidate’s profile: - PhD in Materials Chemistry
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core mechanics (game design) Model the BDI (Beliefs, Desires, Intentions) agent system to be learned by the AI Program the game application specifically for mobile devices Evaluate the game's
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core mechanics (game design) Model the BDI (Beliefs, Desires, Intentions) agent system to be learned by the AI Program the game application specifically for mobile devices Evaluate the game's
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in privacy preserving machine learning (ML) within the SSF-ML-DH project, under the supervision of Olivier Cappé (CNRS, DI ENS) and Jamal Atif (Ecole Polytechnique, CMAP). Funding is available for two