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Field
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reactive molecular dynamics (MD) simulations to understand the reaction mechanisms at the atomic scale involved in the combustion of Aluminum and Iron nanoparticles. Aluminum burns in the gas phase while
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drag reduction in graphene with a combination of electronic structure methods and large-scale atomistic molecular dynamics (MD) powered by machine learning and high-performance computing (HPC). The first
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for the creation of 3D products, as it allows us to overcome the main limitations of current additive technologies. This research is aimed at the development of numerical models based on molecular dynamics approach
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interpret the ageing results obtained from the experiments as well as to identify potential new ageing markers. Computational chemical modelling which also called Molecular Dynamic (MD) simulation is becoming
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Doctoral or post-doc position in the simulation of mechano- or tribochemical processes in advanced hydrogen storage materials (metal, complex and organic hydrides) and degradation of contaminants in
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molecular dynamics simulations of its oxidation. The method will then be applied to new systems, therefore less known, with a view to predicting their behavior under oxidation
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industries, models which are able to quantitatively link the surfactant molecular structure to the final micellar properties are lacking. We propose to investigate these systems by using molecular simulation
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will be the following: Identification of novel hit material through virtual screening and molecular dynamics simulations Chemical synthesis of libraries of potential inhibitors based on hits Performing
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and modeling of polyelectrolyte/protein interactions, molecular dynamics (MD) models are combined with analytical scale models and compared with experimental data from isothermal titration calorimetry
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appointment is for one year with possibility of renewal annually subject to mutual agreement and continued grant funding. GENERAL DUTIES: The successful candidate will develop and use molecular simulation