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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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machine‑learning or data‑analytics tools High‑level programming skills (Python, R, Julia) to build, test, and optimize models of geochemical systems Interest in large‑scale computational simulations (e.g
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Generate synthetic microstructures (based on the open-source OptiMic software) Perform descriptor extraction and micromechanical simulations (MCRpy, DAMASK) Vary the material processing parameters, which
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or discrete probabilistic structures is beneficial but not required. What we offer: WIAS Berlin is a premier research institution known for its strength in optimization, optimal control, dynamical systems, and
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Generate synthetic microstructures (based on the open-source OptiMic software) Perform descriptor extraction and micromechanical simulations (MCRpy, DAMASK) Vary the material processing parameters, which
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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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interest in agentic AI, online learning and optimization, and applications in economics. The full-time positions (100%) are initially offered for two years, with the possibility of extension, depending
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of the school will be optimally trained and positioned in this emerging field. Partners of the school are DESY and Weizmann institute of Science, as well the Humboldt-University Berlin and University Potsdam
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: Algebraic geometry and number theory Area 3: Stochastics and mathematical finance Area 4: Discrete mathematics and optimization Area 5: Discrete geometry Area 6: Numerical mathematics Area 7: Applied analysis