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models capable of inferring the IPLS directly from widely available genomic and epigenomic data. Broadly, the project aims to develop integrative approaches at the interface of (epi)genomics, machine
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Eligibility criteria The recruited person must have expertise in cosmology, numerical development and machine learning. They must be proficient in the Python programming language, with experience in JAX being a
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investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable states, attractors
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, integrating statistical inference, machine learning, and population genetics. We will develop advanced computational methods to characterize the functioning of T- and B-cell repertoires. The goal is to build
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astrophysics, cosmology, or a related field completed by the start date; strong programming skills; working knowledge of machine learning applied to astrophysics and cosmology, in particular simulation-based
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physics and quantum chromodynamics. Knowledge of computer programming is a plus. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR3681-CAMFLO-002/Default.aspx Work Location(s) Number
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-VIS-NIR). Experience in hyperspectral data processing (HMSPL, μXRF, μXAS) and statistical analysis (clustering, machine learning) is preferred. Familiarity with fossilization processes and taphonomic
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present scientific results. # Software and tools - Proficiency in standard computer tools. - Experience with mass spectrometry data processing and analysis software. # Personal skills - Autonomy, rigor, and
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been proposed: traditional computer‑algebra methods [3], reduction of the problem modulo a prime p [6, 2], and symbolic‑numeric methods [4, 1]. This postdoc proposal concerns the second modular approach
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orthogonally to tonotopy. In collaboration with the Institut de la Vision, we will use new “Brainbow”-type fluorescent labeling tools to trace the neuronal connections between the various relays in the auditory