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environment in terms of appropriate chemical descriptors (e.g. polarity, cavity shape, pH) Perform molecular dynamics simulations to sample a dynamic range of protein-pigment conformations Construct a series of
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formation of polyhalogens. The applied methods will include first principles methods like DFT, both for finite and periodic systems, ab initio molecular dynamics simulations and calculations of various
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combination of protein design and molecular simulation techniques. Our primary objective is to uncover the mechanisms governing biomolecular functions through experimental characterization of the designed
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Virus (EBV) and HIV-1 infection dynamics in human lymphoid tissue. This postdoctoral associate will collaborate with experimentalists to utilize EBV and HIV-1 infection data together with multiscale ABM
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biology capabilities within a dynamic, multidisciplinary research environment at King’s College London. The successful candidate will bring deep expertise in tissue processing, digital pathology, spatial
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Degree is in chemistry, biology, or related field. A strong background in computational biology/chemistry (e.g. molecular dynamics simulations) and machine learning is essential. Required License
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experience with multiscale modelling of materials - previous experience with molecular dynamics simulations Applications should be sent by e-mail, together with significant documents, indicating the reference
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our team at DTU Compute, offering a fully funded position within a dynamic and interdisciplinary research environment. The positions are part of the research project “AI-driven materials optimization
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(broadly defined), molecular dynamics simulations, sampling techniques, machine learning, or quantum computing are big pluses. The candidate should have good communication skills, both oral and written, and
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calculations and Brownian Dynamics simulations. The group is looking for a highly motivated and driven postdoctoral researcher to contribute strongly to a wave of ongoing developments deploying this technology