50 modelling-complexity-geocomputation PhD positions at Delft University of Technology (TU Delft)
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make extensive use of low-fidelity simulations which can provide fast but inaccurate solutions depending on the flow complexity. To close this gap, this PhD will explore machine-learning (ML) methods
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experimental data, enabling accurate prediction of nonlinear phenomena such as modal interactions and dissipation pathways across scales: from complex structural assemblies to nanomechanical resonators. In
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the performance of various technical components of the heating systems in different climatic conditions. To address this complexity, a team of geological and technology experts work together to build a framework on
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of asphalt mixtures exposed to climate-induced stresses such as temperature fluctuations, moisture variations, and UV radiation. The study will involve both laboratory experiments and numerical modelling
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maintain robustness through evolution using live-cell imaging and multiscale modelling. Job description Cells are often described as intricate machines where proteins work together in a tightly coordinated
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for levitated systems — from gas sensing to probing physics beyond the Standard Model. You will join a diverse, motivated, and supportive team of academic staff and students in Delft. We foster an inspiring and
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exploration is complex and still not well understood. EXPLORA aims to uncover links between perceptual impacts and active exploration systematically, quantitatively, and empirically. We will create impact
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the experimental setup, analyze data, and gain experience in modeling, coding, and running complex equipment in our state-of-the-art laboratories. You will also receive comprehensive training to support your
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environment perception in autonomous driving by integrating acoustics. Possible research directions include the use of audio-visual foundation models, audio-driven sensor fusion for object detection, cross
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/ML) models can offer a solution here. This project aims to determine to what extent AI/ML models based on electrochemical sensor data are able to identify and quantify local forms of corrosion. We