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, Rouiller I (AUS), Jonic S (FR). MDSPACE: Extracting Continuous Conformational Landscapes from Cryo-EM Single Particle Datasets Using 3D-to-2D Flexible Fitting based on Molecular Dynamics Simulation. J Mol
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or expect to complete a PhD in physics or a related field, with strong background in soft matter / nonequilibrium statistical physics / numerical simulation / statistical inference. Scientific skills
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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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to Inner-Heliospheric Switchbacks” *(JET2SB, https://anr.fr/Project-ANR-25-CE31-7416 ) project of the French “Agence Nationale pour la Recherche” (ANR) is open for applications to work with the space plasmas
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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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. 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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the effects of these factors at the tissue level. The position will also involve simulating and optimizing complex models that integrate biological and physical data using advanced methods, such as physics
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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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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