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. Teaching skills. Other qualifications: Experience with high-fidelity simulations (DNS, LES). Experience with heat-transfer modeling, especially in complex-geometry flows. Experience with RANS model
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specimens. The postdoc will contribute to the development of hybrid modeling and identification approaches that combine classical constitutive frameworks, numerical simulation, and machine learning. The work
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analysis by integrating diverse datasets (e.g., in situ observations, remote sensing products, model simulations) to inform model development, calibration, and validation. Collaborate with a
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methods, such as Convolutional or Bayesian Neural Networks, Simulation-Based Inference (SBI), Normalizing Flows, or Diffusion Models, is also a plus. The position includes a competitive salary, research
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response to climate forcings for different past climates. · Perform and analyze global model simulations. · Collaborate with IPSL Earth System model developers to ensure consistent integration
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methods for multiphase flow models Integrate experimental, pilot-scale, or high-fidelity simulation data into model calibration and validation workflows Design and run numerical simulations of multiphase
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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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models to realistic urban environments. The effects of short-term microclimatic variability and vehicle-induced vortices on VTOL UAV operations shall be quantified. high-fidelity CFD simulations and
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simulation-based benchmarks and on-board hardware tests. A trained model can be run on-board purchased hardware during test-flights to prove utility Tasks: independent and cooperative qualification through
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collaborators. The activities will include: • Electromagnetic modeling and numerical simulations (e.g., FDTD, FEM) • Design of metasurface architectures based on dielectric materials available at CRHEA