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insights into MCTP action and ER tubularization at PD, the post-doc will use molecular modeling and dynamics. - undertake simulations - present results in team meetings - present results as scientific
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molecular modeling and dynamics. Modeling and simulation of membrane systems. Writing of results for publication. Data handling. -The "Institut de Biologie Physico-Chimique", in association with the CNRS
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ExperienceNone Additional Information Eligibility criteria Python programming. Analysis and development of ML and DL models using standard data science libraries. Data engineering from molecular dynamics
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contribute to various aspects of the project, such as: - developing new theoretical approaches to model electrode/electrolyte interfaces - performing molecular simulations, such as molecular dynamics
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molecular dynamics simulations with LAMMPS, and data curation. Scientific context: Our current understanding of polymer viscoelasticity is founded on single-chain models [2]. Such models draw on the fact
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, statistics, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology
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lakes - Good knowledge of mathematical and statistical modeling methods in ecology - Proficiency in optical microscopy and flow cytometry tools - Very good knowledge of algal community identification
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The postdoctoral fellow will participate in the PostGenAI@Paris AI Cluster (ANR) project at Sorbonne University, and more specifically in the "AI-Augmented Multiscale Modeling for Energy Storage" sub-project, whose
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of an iPSC model of mutations observed in patients - Characterization of defects at the cellular level - Characterization of defects at the transcriptomic level The successful candidate will work in the “mRNP
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with specialisation in computational or theoretical chemistry. • Strong expertise in electronic‑structure calculations (molecular and periodic DFT). • Experience with modelling organic semiconductors and