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be done via computer simulations, including Monte Carlo and molecular dynamics, combined with the use of statistical mechanics to predict e.g. phase transitions, nucleation rates, etc. The work will be
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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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tools for static and dynamic analysis are powerful for detecting vulnerabilities, they suffer from both theoretical and practical limitations. Their results are often plagued by false positives (reporting
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Assistant Professor Pablo Daniel En- rique (University of Waterloo) Project goals The main goal of this doctoral research is to develop and apply thermomechanical simulations to study the LPBF processing
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processes that produce energy and raw materials. The Department of Thermodynamics of Actinides is looking for a PhD Student (f/m/d) - Machine Learning for Modelling Complex Geochemical Systems. The job
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passionate about sustainability, clean energy, and water treatment technologies?Are you skilled in machine learning, process modelling, or chemical engineering simulations?Are you excited by the idea
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-language models, or diffusion models to simulate and design complex urban traffic environments? Do you want to shape the next generation of data-driven mobility intelligence with your creative ideas and
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department at TU/e for finite element-based deformable body simulations. Conduct research on mechanical contact processing models, integrating both physics-based numerical models and data-driven approaches
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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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. Process simulation software is being developed for virtual optimization of tool design and material handling, enabling first-time-right manufacturing. The predictive quality of these tools relies