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edge AI hardware/software. Contribute to designing and evaluating scheduling algorithms for virtualized or distributed AI resources under varying load, latency, and failure conditions. Build and test a
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. The successful candidate will be based in Odense, under the primary supervision of Prof. Ricardo J. G. B. Campello , but they will be expected to also work closely with other PhD students, postdocs, and
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contribute to the development of novel algorithms and methodologies that enhance the robustness and accuracy of acoustic measurements. We are looking for a highly motivated candidate, with a relevant MSc
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at the Institute of Visual Computing, course on Fundamentals of Geometry Processing, or Data Structures and Algorithms. Co-supervision of bachelor and master thesis. Research and development
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availability, more attractive working hours at service locations, and decreased train unit movements for regular maintenance. New innovative approaches need to be developed to schedule rolling stock
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learning, non-Hermitian systems The Quantum AI lab at ETH (Prof. Juan Carrasquilla ) invites applications for PhD positions to work at the intersection of computational quantum many-body physics, machine
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this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent
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electrical power, enabling smart sensors to operate without batteries. You will explore novel capacitor-based rectifier architectures, adaptive impedance-matching algorithms, and on-chip protection mechanisms
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communication Autonomous driving algorithms and technologies (e.g. vehicle control, path planning, scheduling) and sensors (e.g. lidars, radars, cameras, and GNSS) High-level integration of autonomous driving
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Join TU Delft and work together with NXP to build low-power AI accelerators for self-healing analog/RF calibration, fixing noise/offset. Co-design algorithms & hardware and validate on real silicon