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Field
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candidate will drive the development of the FSI CMF model to simulate the effect of fluid-solid coupling on the vibration of the structure. The successful candidate will work with the multidisciplinary
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challenges and decision-making under uncertainty. Ability to translate conceptual models to their mathematical formulation and to test them with numerical and simulation experiments. Excellent communication in
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of the mechanical properties of cell walls based on experiments and small-scale simulations developed elsewhere in theGreenTE consortium. Correct and improve your mathematical models in close collaboration with
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interact to shape an entire simulated organ. To calibrate and parametrize the models, you will have access to data from experimental collaborators (Boxem Lab). In turn, your models will help our experimental
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in a number of the following topics: Turbulence modeling with wave propagation simulations Modulations used in optical wireless communications Data Analysis and Management Implement and open-source
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numerical simulations from spectral wave and ocean models to produce high-resolution historical and future climate data. We encourage candidates with domain knowledge of wave modelling to apply, as
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) methods to tackle challenging molecular engineering problems in life sciences and materials design. Situated in the Data Science and AI division, our group advances generative models, molecular simulations
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challenging molecular engineering problems in life sciences and materials design. Situated in the Data Science and AI division, our group advances generative models, molecular simulations, and molecular design
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CFD, turbulence models. Experience in visualizing and analyzing simulation data and interpreting results. Strong written and verbal communication skills in English The following experience will
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: Coordination Layer: Formulate passivity-based conditions that guarantee agents—modelled as general nonlinear systems—synchronize their outputs or follow desired collective patterns purely through local