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candidates working in formal methods and/or computer systems with interests in one or more of the following areas: machine-checked verification of systems software, GPU kernel semantics and verification, and
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, implementation, and open-source release of the lab’s tools and artefacts Participate in the supervision of PhD and master students Profile PhD (or nearing completion of) in computer science or a closely related
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this new hybrid network. Your code will directly enable the next generation of energy-efficient AI clusters. Project scope You will bridge the gap between custom optical hardware and standard AI software
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to teaching activities may be discussed, including the possibility of supervising Master’s students. Profile Applicants should have: • a PhD in physics or related fields, completed or expected to be completed
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For both positions: Conduct innovative, independent research aligned with the lab's mission and the candidate's interests Contribute to the lab's open-source software, datasets, and benchmarks Mentor PhD and
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robust acquisition, synchronization, calibration and quality-control procedures across multimodal data streams. Troubleshooting software, hardware, sensors, timing, synchronization, data acquisition and