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Field
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automation Earth processing Computational fluid dynamics Numerical process modelling Rheology Furthermore, the candidate should be motivated to work collaboratively as part of a team. You must have a two-year
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that merge thermo-fluid dynamic laws, deep learning, and experimental data. A central goal is to overcome current limitations in TES operation and optimization, enabling discovery of new high-performance and
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initiation in the following areas are helpful: Strong background on computational fluid dynamics (CFD) and design software using ANSYS and SolidWorks. Experience on high performance computing is desirable
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hydrodynamics for novel marine vehicles, including large ships and small AUVs and offshore renewable energy systems including offshore wind. You are expected to perform advanced computational fluid dynamics
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to the proportion and composition of mineral, melt and fluid phases across a range of geologically-relevant pressure, temperature and composition. With constraints on the partitioning of trace elements among
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Computational Fluid Dynamics (CFD) models; data-based models determined from training/calibration data by system/parameter identification and machine learning. The key challenge is striking a balance between, on
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Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Do
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++ programme “Break-through technologies in flow and fluid composition measurement”. It involves close cooperation with flow sensor companies and the TU Delft, where a post-doc will focus on the electronic
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at the micrometre scale that can propel themselves through fluids, mimicking natural swimming organisms such as bacterial forms. Using biological building blocks found in cells and encapsulating them inside vesicles
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and modelling techniques. Real-World Impact: Contribute to transformative technologies in clean energy and carbon capture. Future job opportunities: Digital modelling and computational fluid dynamics