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imaging systems capable of penetrating fog, dust, and even certain solid materials. These systems will deliver detailed, high-resolution imaging in challenging conditions where conventional optical sensors
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of PhD and postdoc researchers excited about making theoretical and algorithmic contributions in intelligent decision making. Apart from dealing with the scalability challenge inherent in modern AI
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seeking a highly motivated PhD student to join our team to work on the design and implementation of Oscillatory Neural Networks (ONNs) for physics-based computing applications. You as the candidate will be
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identity, behavior, and trajectory. You will extend these models to understand how genetic risk factors alter cell–cell communication networks. Spatial transcriptomics datasets will be used to anchor
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our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors
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faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies
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. The second sub-project, a postdoc track, focusses on pedagogies or structures for guiding students in selecting competencies to be achieved as learning outcomes, through learning activities and assessment
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to work on the design and implementation of Oscillatory Neural Networks (ONNs) for physics-based computing applications. You as the candidate will be an integral part of the prestigious NWO AiNED AI-on-ONN
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jointly embedded in the research groups of Dr. Sid Kumar (Mechanics, Materials, and Computing group) and Dr. Georgy Filonenko (Functional Polymers and Sensors group). Research group of Dr. Sid Kumar
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Polymers and Sensors group). Research group of Dr. Georgy Filonenko: Functional Polymers and Sensors group: www.tudelft.nl/me/over/afdelingen/materials-science-and-engineering/research/functional-polymers