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focused on modeling and simulations of turbulent mixed-phase clouds. This interdisciplinary project encourages collaboration with experts in atmospheric physics. The successful candidate will contribute
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, pilot-scale, or high-fidelity simulation data into model calibration and validation workflows Design and run numerical simulations of multiphase flow systems and reactors Quantify model uncertainty and
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Keen to push the frontiers of multiphase reactor modeling and accelerate the scale-up of emerging net-zero technologies? Join us at the Department of Chemistry and Chemical Engineering! About us Our
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design. One of our group's goals is to create efficient surrogate models that reduce the computational cost of MD simulations by several orders of magnitude. Notable examples of our work in this area
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experimental, pilot-scale, or high-fidelity simulation data into model calibration and validation workflows Design and run numerical simulations of multiphase flow systems and reactors Quantify model uncertainty
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, components, overall system performance) Numerical methods and simulation tools (e.g., Python/Matlab, CFD modelling, optimization) Beyond technical skills, we value people who contribute to a healthy and
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cost of MD simulations by several orders of magnitude. Notable examples of our work in this area include Boltzmann Generators [1 ,2 ], Surrogate-model Assisted Molecular Dynamics [3 ], and Implicit
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forms suitable for system-level reasoning, and ensuring consistency between detailed simulations, experimental data, and higher-level system models. The researcher is expected to contribute