16 molecular-modeling-or-molecular-dynamic-simulation PhD positions at Radboud University
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the intricate dynamics of molecular collisions and reactions? Want to operate world-unique equipment? Join us as a PhD candidate and contribute to exciting research on cold and controlled reactive molecular
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you intrigued by the intricate dynamics of molecular collisions and reactions? Want to operate world-unique equipment? Join us as a PhD candidate and contribute to exciting research on cold and
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dynamic interdisciplinary research institute that brings together chemistry and physics to unravel the mysteries of atomic, molecular and solid-state environments. The institute strives to make a positive
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dynamics and learning in artificial and biological neural networks, with the aim of: Unveiling the link between network structure and neural representations. Understanding the impact of structural and
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, viscosity, and surface or interfacial tension. We will train a range of AI models to allow us to predict these properties from the chemical structure alone. Once established, we will expand the self-driving
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, simulations and cutting-edge data to uncover the origins of black holes and neutron stars, linking theory with the latest discoveries in this rapidly growing field. It has been just over a decade since the
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source for multispecies trace gas detection. This system has shown an excellent performance during in-situ measurements of a wide range of molecular species with high sensitivity (Opt. Express 32, 14506
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pioneering PhD project exploring how massive stars evolve into gravitational-wave sources. Combine stellar physics, simulations and cutting-edge data to uncover the origins of black holes and neutron stars
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the other SPINES PhD projects on (a) ‘Infrastructure Managers as Institutional Entrepreneurs’ (University of Groningen), and (b) ‘Modelling Shared Pathways and Tipping Dynamics’ (University of Twente
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key physical properties of mixtures of molecules, including solubility, viscosity, and surface or interfacial tension. We will train a range of AI models to allow us to predict these properties from