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the development of foundation models that have expanded the boundaries of machine capabilities. However, learning these models requires direct access to vast data repositories, which poses significant privacy and
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reasoning to define and analyze system components and their interactions. Merging machine learning with symbolic AI to enhance system (performance) monitoring. Advancing adaptive surrogate modeling
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revolutionize neuroscientific visualization. As a PhD candidate, you will develop cutting-edge brain visualization software, integrating real-time rendering techniques. You will work at the forefront
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pyrolysis carbons into value added graphene(oxide) colloids. Your PhD project is part of a larger collaboration between TU Eindhoven and Shell on sustainability. The overarching goal of this collaboration is
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developments in self-supervised learning and generative models? • Are you excited to work on perception tasks for safety-critical systems using the next-generation automotive radar? • Then apply for the PhD
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. The candidate will be expected to acquire the University Teaching Qualification (UTQ). Requirements Specific Requirements PhD in Software Engineering, Computer Science or related discipline(s). Candidates
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a soft robotic actuator using neuromorphic learning control. The overall goal of this PhD project is: To develop and integrate adaptive spiking circuits based on organic neuromorphic and biohybrid
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tools). Experience with hardware architecture, FPGA, and system-level simulation is desirable. A good theoretical understanding of statistics and machine learning theory. Strong analytical skills and
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Job related to staff position within a Research Infrastructure? No Offer Description ASML Photolithography machines play a central role in the production of ever smaller and faster microchips and
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Job related to staff position within a Research Infrastructure? No Offer Description ASML Photolithography machines play a central role in the production of ever smaller and faster microchips and