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systems and control theory. Knowledge of fluid dynamics and related physical modeling. Strong programming skills (e.g. Python, MATLAB, or similar) for data analysis and model development. Ability to work
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FLOW research group is a young, dynamic group working in the fields of thermodynamics, fluid mechanics, and data-driven modelling. At the Department of engineering Technology (INDI) — Thermo and Fluid
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to the active sites within the porous structures. The successful doctoral candidate (DC) will develop a microscopic model for mass transport and reaction in redox flow batteries electrodes. Within this project
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transport and reaction characteristics within the microstructure. The successful doctoral candidate (DC) will develop a microscopic model for heat transport and reaction in redox flow batteries electrodes
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Perpignan, and will then continue at the LaTEP laboratory in Pau. Doctoral school: ED 305 – Doctoral School of Energy and Environment at UPVD (University of Perpignan Via Domitia). Context In the current
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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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various objectives (model tuning), such as energy indicators (e.g., efficiency, exergy analysis) or parameters affecting investment costs (e.g., heat exchanger pinch, fluid flow rates), in order to build a
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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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Vacancies PhD position on the design and fabrication of MEMS drag force-based flow and fluid composition sensors Key takeaways In this project, we will combine well-known thermal flow sensing
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Position: Bioprinting next generation functional tissues The field of tissue engineering and bioprinting is continually advancing to develop functional tissue models that more accurately mimic native tissue