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implement machine learning models dedicated to the prediction, interpretation, and quantitative analysis of Raman vibrational spectra, establishing explicit links between structure, local chemical environment
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-month PostDoc position in modelling land-cover change at watershed-scale. Project Overview Deep-C brings together a consortium of experimentalists and modelers to explore the coupled carbon (C) cycling in
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both natural and highly polluted conditions, and how these processes can be represented in models to theoretically assess the potential of cirrus cloud thinning as a climate intervention strategy. The
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/ Physics beyond the Standard Model Appl Deadline: 2026/02/28 04:59 AM UnitedKingdomTime (posted 2026/02/11 05:00 AM UnitedKingdomTime, listed until 2026/08/12 04:59 AM UnitedKingdomTime) Position
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theoretical models and numerical tools (master equations, quantum trajectory simulations) to investigate coupling regimes, dynamical phase transitions, and the effects of collective dissipation on coherence and
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a modeling approach inspired by statistical physics to describe individual strategies, their interactions, and emergent effects at the group scale. The candidate will contribute to the development and
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. Numerical modeling of Mercury's magnetosphere and ion dynamics 2. MSA instrument data analysis LPP (Laboratory of Plasma Physics) is a joint research unit of the CNRS, École Polytechnique, and Sorbonne
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that incorporates a broad range of neutrino and dark-matter models, assessing their effects on large-scale-structure (LSS) statistics as measured by the power spectrum and bispectrum of galaxies or intensity maps
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Experience1 - 4 Additional Information Eligibility criteria Required skills • PhD in Earth system science, computational modeling, or a related field. • Solid experience in paleoclimatology, climate
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applications for a postdoctoral position on logical foundations and formal methods for quantum programming languages. Topics of interest (non-exhaustive) : • Models of quantum computation (λ-calculi, term