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note: You can apply online. We will not process applications sent by email and/or post. As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do
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(there is room for learning-on-the-job). A PhD in aerospace/mechanical engineering or applied physics. Demonstrated ability to conduct research in experimental fluid mechanics. Proven competence on flow
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Science, Physics, Mathematics or Computer Science. You have a solid background in computational fluid dynamics (CFD) and be proficient in programming (e.g., Python, Fortran, or C++) and visualization tools
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that influence human interaction and learning. While multimodal systems are already being developed to monitor physical and cognitive engagement, current approaches offer limited interpretability and often do not
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: Within this international project, TU Delft will develop a machine learning-based forward operator to enable the assimilation of SAR imagery into the crop growth model. You will: Process SAR imagery over
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biochemical reconstitution, fluorescence microscopy and structural biology to determine how this process is regulated at the molecular level. The project will make extensive use of the group’s in-house Talos
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healthcare, technology, innovation, physics and radiochemistry? Are you looking for a challenging role where you can apply your expertise to help improve patient care? Then this is your opportunity! For a
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do, both in your work and in your development. Read more about our terms of employment . Selection process At Utrecht University, we strive to be a place where everyone feels at home. We value
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relevant field, such as plant science, crop science, agricultural engineering, biosystems engineering, horticulture, applied physics, data science or a related discipline. Demonstrable research experience in
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on static process design and control that don’t account for feedstock variability, inefficient solvent use, and high energy demand, hindering scale-up. Information This project will be executed together