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will join the growing team of researchers on the ERC project CONTEXT, working at the intersection of scientific machine learning and fluid dynamics, under the supervision of Anh Khoa Doan. You will also
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, mechatronics, thermal, fluids). Expertise in engineering design (mechanics, team-based, numerical, computer-aided). Ability to develop and teach upper-level undergraduate and graduate courses. Demonstrated
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The objective of this post-doctoral research is to
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, stochastic differential equations, computational methods in fluid mechanics and turbulent flows, high-performance computing, machine learning methods in computational problems. GSSI is a world-renowned
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-structure interaction (FSI) with focus on the fluid mechanics. We couple computational fluid dynamics (CFD) to a structural solver and/or a controller for the detailed simulation of a machine. We develop
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accuracy is still limited. In contrast, computational fluid dynamics (CFD) models can capture the arc physics and molten pool dynamics, including arc energy transfer and liquid metal convection within
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applications. The project integrates: Computational Fluid Dynamics (CFD) and multiphase flow modeling Radiative heat transfer Machine learning and reduced-order modeling Data-driven optimization for industrial
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) systems. Proficiency in MATLAB, Python, and LabVIEW programming languages is essential. Demonstrated research experience with a strong record of peer-reviewed publications in fluid dynamics, turbulence, air
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engineering, physics, atmospheric sciences, or a closely related field. - Strong publication record and demonstrated experience in computational fluid dynamics, turbulence modeling, and wind energy
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eólicas flotantes. Laboratory experiments and Computational Fluid Dynamics simulations—particularly using the Smoothed Particle Hydrodynamics (SPH) numerical technique—of the sloshing phenomena occurring