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investigate different rhythmic competencies, and how these relate to different speech and language skills. The postdoc will integrate into a team investigating these different topics, and will also be
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models, assessing their effects on large-scale-structure (LSS) statistics as measured by the power spectrum and bispectrum of galaxies or intensity maps. The project emphasizes spectroscopic galaxy surveys
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modeling and simulation, and statistical inference (lead by mathematicians and biologists) - The recruited postdoc will be asked to work in the labs on a daily basis. - The recruited postdoc will be expected
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integrating a wide range of neutrino and dark matter models, and aiming to evaluate their effects on large-scale structure statistics (LSS), as measured by the power spectrum and bispectrum of galaxies
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at the IJM. This recently created team studies ancient genomes to better understand human evolution and its implications for biology and health. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre
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well as next-generation ecological models that take uncertainty into account. The https://leca.osug.fr (LECA) is part of the University of Grenoble Alpes and the CNRS in France. Grenoble is located close to
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clinical neurology, neuroimaging, and computational modeling. Postdoc Mission: Lead the project efforts in close interaction with on-site neurologists experienced in ALS, experts in Clinical and
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collaborate with ARCHIVES project partners to ensure coordinated progress and sharing of results. · Develop solutions combining numerical modeling, mathematical methods, and statistical/AI approaches
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postdoc will: ● Start by familiarizing with existing research and methods for genome interpretation, such as the AI4GI lab previous publications (https://academic.oup.com/nar/article/50/3/e16/6430850?login
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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
-Negative Matrix Factorization will be explored. The second challenge is to leverage the derived statistical models to design automated data-driven procedures for the estimation of epidemiological indicators