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We are looking for a highly motivated, skilled, and persistent PhD student with experience in computational fluid dynamics (CFD) and some knowledge in structural analysis. The research aims
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the controlled flow at tunable temperature and photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning
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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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capture technologies. In this project, you will: Develop a 3D Digital Model: Create an advanced computational model of high-pressure mechanical seals. Apply Computational Fluid Dynamics (CFD): Simulate gas
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spoken communication skills The following skills are desirable but not essential: Demonstration of undertaking research projects Ability to program Previous experimental experience in fluid dynamics
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matter physics, physical chemistry, computational chemistry, statistical mechanics, or related fields Good English language – spoken and written Nice-to-have: Experience with molecular dynamics simulations
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, combustion, and process optimisation. The project is focussed on the development of novel interface capturing Computational Fluid Dynamics methods for simulating boiling in Nuclear Thermal Hydraulics
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Requirements: very good or good university degree in physics, meteorology, fluid dynamics or comparable Description of the PhD topic: (subproject T7) In Urban air mobility, a high wind sensitivity of UAVs
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Technology and Logistics and co-supervised by at least one additional professor plus an international tutor of the RTG Requirements:very good or good university degree in physics, meteorology, fluid dynamics
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applied physics other related disciplines. Demonstrated knowledge in at least one of the following areas: porous media flow computational fluid dynamics (CFD) pore-network modelling lattice Boltzmann method