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will involve both computational predictions and experimental validation. The project will combine density functional theory calculations with machine learning and molecular dynamics simulations
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hybrid organic-inorganic glasses and compare their vibrational properties against each other as well as more established glass families. The project will complement molecular dynamics simulations with
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. To do so, you will combine atomistic simulations (density functional theory and ab-initio molecular dynamics simulations) with new machine learning models to parameterize machine learning force fields
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for catalysis of sustainable chemical processes. Visualizing Chemical Dynamics in Real Time Apply advanced atomic-resolution imaging and image analysis to uncover surface dynamics, reactivity and molecular
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for catalysis of sustainable chemical processes. Visualizing Chemical Dynamics in Real Time Apply advanced atomic-resolution imaging and image analysis to uncover surface dynamics, reactivity and molecular
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complex materials simulations. These agents will assist with setting up, executing, and optimizing electronic structure workflows, from standard ground-state Density Functional Theory (DFT) calculations
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well as other professional qualifications relevant for the PhD project like familiarity with molecular techniques in plants, particularly Solanaceous crops like potato and tomato will be taken into consideration