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resistance potential of ash trees. The project aims to support conservation efforts by refining selection criteria for resistant ash based on a comprehensive understanding of disease dynamics and environmental
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The aim of this project is to describe ion conduction and activation/inactivation processes by employing molecular dynamics and statistical mechanical methods. The expected outcome is an improved
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drug development to inhibit or deregulate disaggregase activities. We want to dissect the molecular basis of ClpG and ClpL activity control. How is the activity of the disaggregases repressed in absence
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as ligands. The fundamental science behind the selective enrichment of lithium-6 by solvent extraction is poorly understood. This project will combine molecular quantum mechanics and molecular dynamics
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modelling of materials and machine learning. Experience in atomistic modelling (molecular dynamics, density functional theory) and machine learning is important, as well as a strong interest in pursuing
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, your application should include (PDF format): A letter of motivation (max. 1 page) A detailed curriculum vitae. Please include an overview of your experience with molecular dynamics, density-functional
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tools from chemistry and biology, and apply these in studies of therapeutic peptides and proteins. Our aims are to develop modulators for protein-protein interactions (PPIs) and to provide molecular-level
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, making a new model which is suitable for a variety of polymer systems. This will involve integrating molecular dynamics simulations, electronic structure calculations, and machine learning techniques
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of molecular data in cancer genomics. The position is connected to the project “Bayesian Rank-based unsupervised Integration of multi-source Data in cancer Genomics and the digital Economy (BRIDGE)”, recently
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spend some time on placements in the industrial partner. We are seeking ambitious, inquisitive and innovative individuals to join our multidisciplinary research team. As part of a dynamic and