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Field
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is to be the “EO innovation hub” connecting EO with a growing ecosystem of disruptive and transformative innovations such as AI, machine learning, quantum computing, edge computing, metamaterials and
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for representing, compressing, and computing with complex physical systems. The project is carried out in close collaboration with researchers in Electrical Engineering working on emerging memory architectures and
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materials engineering, plastics and metals present complementary strengths and challenges. Metals offer strength, conductivity, and wear resistance while polymers enable complex geometries and lightweight
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scale electrical storage remains challenging and costly. A promising alternative is high-temperature thermal storage. Molten salts are among the most promising candidates for this purpose due
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against simpler machine-learning baselines; • train and evaluate ARCA on large-scale microbiome datasets, with attention to sparsity, batch effects, scalability, generalisation across studies and
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Engineering TU Delft seeks a motivated postdoctoral researcher for a full-time, fully funded, 30-month project on Functional Electrical Stimulation (FES) shorts to improve gait after stroke. You will work
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Electrical Stimulation (FES) shorts to improve gait after stroke. You will work closely with Sint Maartenskliniek and Biomex, embedded in the multidisciplinary "Care is coming home!" program, a 5-year
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their added value against simpler machine-learning baselines; train and evaluate ARCA on large-scale microbiome datasets, with attention to sparsity, batch effects, scalability, generalisation across studies
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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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architecture to tape-out and characterisation, using suitable CMOS technologies. You will conduct electrical measurements and validate your solutions at robotic system level. Your research will combine