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-scale simulations from the PEPR BRIDGES Conduct sensitivity studies based on simulations in which the coupling between the ocean, the atmosphere and waves will be gradually degraded (as done e.g., by
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from motivated candidates with a strong simulation and/or theoretical background; the project scope can be adapted to the successful applicant's expertise and interests. - Design, preparation, and
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FieldHistory » History of scienceYears of Research ExperienceNone Additional Information Eligibility criteria The candidate must hold a PhD degree in the field of analysis (theoretical and/or numerical) of PDEs
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Post-doctoral position (M/F) for testing drought-based BEF relationships at CEFE Montpellier, France
) Carry-out additional simulations with the Phoreau model to test the effect of tree diversity on forests' resistance to droughts. ii) Analyse biodiversity-drought resistance relationships, across a
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of the UltiMatePV project and will coordinate tasks with the project's various partners. Participate in the technological maturation of devices. Conduct numerical simulations (optoelectronic devices, transport
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, statistical and case of study of switchbacks. Comparaisons with synthetic observations from the dedicated simulations of the JET2SB project. 2) Collaboration with the local LPC2E team, as well as the full
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code; • Simulating spallation source transients in MYRRHA and EFIT and reactivity measurements using various types of detectors; • Comparing the space-energy effects calculated by simulation in MYRRHA
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correlations. - Analyse experimental data mixing both quantum optics and solid-state physics phenomena - Supervise PhD students and interns - Ensure an efficient collaboration and information sharing with
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. Using all-atom molecular dynamics simulations and enhanced sampling techniques, the project will investigate how S-glutathionylation modulates nucleosome structure and dynamics, alone and in combination
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quantification of pigments and binders. The work will include the generation of simulated spectral data based on physical models, the training and optimization of machine learning models, and their validation