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molecular docking, molecular dynamics and free-energy methods (MD/FEP), machine learning for molecular design, and protein–ligand modelling. Experience bridging computational and experimental groups, and the
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l'ENS, within a research environment specialized in soft matter, statistical physics, and fluid dynamics. The project will rely primarily on large-scale molecular dynamics simulations and theoretical
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22 Apr 2026 Job Information Organisation/Company Lodz University of Technology Department Department of Molecular Physics, Faculty of Chemistry, Lodz University of Technology Research Field
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of cryo-electron tomography (cryoET), molecular dynamics simulation, and machine learning. The project aims to develop AI methods for mesoscale structural biology, understanding how cellular macromolecules
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labs across HHMI. This role is part of the AI+CryoET project within AI@HHMI, a multi-institutional project at the intersection of cryo-electron tomography (cryoET), molecular dynamics simulation, and
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release of encapsulated contents. These systems provide a relevant model to study dynamic compartmentalization and chemical communication.[5-6] In both cases, the objective is to understand how molecular
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, structure and dynamics, with the aim of understanding biological systems and processes at the molecular level. The emphasis is on experimental and theoretical studies of the physical properties of proteins in
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, structure and dynamics, with the aim of understanding biological systems and processes at the molecular level. The emphasis is on experimental and theoretical studies of the physical properties of proteins in
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Sehgal at the University of Pennsylvania, focuses on the genetic and molecular mechanisms underlying sleep and circadian rhythms. The lab uses a combination of model organisms, including Drosophila and