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building demonstrators · Knowledge of Comsol multiphysics software for finite element modeling of the piezoelectric transducer is a plus · Skills in simulation of electronic circuits (LTSpice
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years the atmospheric modeling community achieved major advances in its capability to numerically simulate iodine chemistry in the atmosphere. This project will take advantage of the 1D chemistry and
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biology approaches to simulate biological models at different time-scales in the context oft the development of the PhysiCell/PhysiBoSS modelling systems(Ponce-de-Leon et al., 2023). In particular, we
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Job description: DESY The CMS Quantum Computing group develops generative machine learning models for detector simulations, specifically the simulation of showers in calorimeters: Proof-of-principle
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . Our team is seeking a highly motivated Research Assistant to contribute to cutting-edge research in embodied AI and
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the principles and institutions of popular government, understood as those which empower ordinary citizens rather than socio-economic elites. The project contrasts popular government with the dominant model
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to lead an investigation exploring the ability of recently developed global earth system models to simulate coastal sea level across sub-annual timescales. This work will leverage a suite of coupled models
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at WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective-postdocs-2/ . Lab website: https://cruchagalab.wustl.edu/ . Trains under the supervision of a faculty mentor including (but
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numerical simulations using ANSYS Fluent or equivalent CFD software, including modelling of fluid flow, turbulence, radiation, heat and mass transfer, and chemical reactions occurring in biomass conversion
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arrays) from experimental data, leveraging training on simulated datasets. Interpretable neural networks for physics: Development of interpretable deep learning models for identification of matter phases