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, developing molecular models of electrolytes based on polymers, LiFSI salt, and ionic liquids, in contact with active material surfaces. Simulations will be carried out in confined geometries representative
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environment linking molecular biology, biophysics, and computational modeling. Include these in your application: A comprehensive CV detailing your publication history A copy of your PhD diploma Contact
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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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Department of Clinical Microbiology The Dwibedi research group at the Department of Clinical Microbiology and the Laboratory for Molecular Infection Medicine Sweden (MIMS; https://www.mims.umu.se
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, protein and lipid chromatography (FPLC, HPTLC), various spectrophotometers (UV-visible, CD, fluorimeters), and computers for molecular dynamics simulation. The IPMC institute includes various state
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proteins remodels the eukaryotic cytoskeleton, including during cancer and viral pathogenic processes. The Atherton group is based in Randall Centre for Cell & Molecular Biophysics , home to a diverse array
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. Our group combines state-of-the-art methods in experimental ultrafast spectroscopy and molecular dynamics simulations: We develop and apply novel ultrafast spectroscopic methods aimed at uncovering how
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Communication and Signaling 2025;23(1):209. Cellular and Molecular Life Sciences 2025;82(1):167. Journal of Bone and Mineral Research 2024;39(12):1783-1792. Molecular Therapy Nucleic Acids. 2024;36(1):102405
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on understanding the molecular mechanisms behind retinal development and disease using human pluripotent stem cells. We specialize in creating retinal organoids, “eye-like” organoids, and other retinal cell types
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 9 days ago
complexes. The successful candidate will develop novel graph neural network (GNN) architectures to learn dynamic information from molecular dynamics (MD) simulations of protein-protein and protein-nucleic