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                . Correlating experimental, ab initio and multi-scale simulation as well as machine learning techniques is central to our mission: Development and application of advanced simulation techniques to explore and 
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                Project (PhD Position) – Quantum-Classical Co-Simulation Framework Development for Neurobiological Systems Your Job: The overarching goal is to implement a code for multiscale quantum mechanics / molecular 
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                inviting applications for a PhD Student (f/m/x) in the field of Theory and Methods for Non-equilibrium Theory and Atomistic Simulations of Complex Biomolecules Possible projects are variational free energy 
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                for the simulation of non-adiabatic exciton transfer dynamics in light-harvesting complexes. The research will use a combination of quantum and molecular dynamics simulations, electronic structure calculations, and 
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                demands. To break this bottleneck and cut simulation time by orders of magnitude, you will design and implement surrogate models that learn the behavior of full‑physics codes using modern machine‑learning 
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                research and scientific exchange. To that end, we closely interact with experimental laboratories. You will: Develop, simulate, and analyze biophysical models of infection spreading and the inflammatory 
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                complex materials with tailored properties using high-throughput simulations, data analytics, and material characterization. Benefit from strong connections to top research infrastructures like the Jülich 
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                management (RDM) system. The goal is to create an overarching data space for the RTG that integrates various experimental techniques and simulation methods. This includes concepts for ensuring data quality 
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                -bayreuth.de Dr. Gerd Steinle-Neumann . Atomistic simulations on physical properties of planetary materials with the goal of improving our understanding of the state and evolution of planetary interiors. Email 
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                and Data Science (MIDS) at the KU Eichstätt-Ingolstadt. The research group works at the intersection of analysis, modeling and simulation. The advertised position is partly funded by the German Research