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also include generative or predictive modeling of dynamic radar scenes. The project combines methodological machine learning research with experiments on real automotive sensor data. You will have access
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have: MSc in engineering or similar discipline by the start date of the position Experience with mechanical modeling and simulation Experience in computer programming/scripting (e.g., C++, Python, Matlab
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WDM switches and the fast control to enable novel low latency highly scalable and flat interconnect AI compute clusters. Machine learning clusters and artificial intelligence (AI) training have become
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compositionally complex recycled steels, using density functional theory and machine-learned interatomic potentials, in close collaboration with leading academic partners and Tata Steel. Job description At TU Delft
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reliable hydrogen-resistant circular steels. In this role, you will develop fundamental insights into the mechanisms governing hydrogen-induced degradation and failure of circular steels. As a PhD researcher
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Job description We invite applications for a fully funded PhD position in the area of Scientific Machine Learning (SciML), which integrates data-driven machine learning techniques with established
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at the intersection of computer vision, micro-electronics analysis, and hardware security, and will work under the supervision of researchers within the Department of Intelligent Systems. The PhD researcher will be
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low latency and high capacity optical switched AI computer network architecture empowered by the developed photonic integrated WDM switches and controls. The PhD candidates will contribute to the TU/e
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; Proven competence on flow measurement techniques and PIV; Familiarity with optics, lasers, image processing and statistical data analysis Familiarity with flow modelling techniques (CFD) or machine
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Are you intrigued by how you can shape the energy transition by scale up of green electricity based large-scale energy storage via CO2 capture and dynamic conversion with hydrogen from electrolysis