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verification tools. AMS test diagnostics and fail-log analysis. Your Role as a PhD Candidate You will: Analyze and enhance current automotive IC test flows. Develop new or improved fault models using NXP’s in
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new paradigm in the validation of autonomous driving software, focusing on the intersection of Large Language Models (LLMs) and Autonomy 2.0 / End-to-End (E2E) approaches. While E2E models promise
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Institute and will be working together with researchers from QuSoft . This PhD project aims to push the state-of-the-art in quantum compilation, verification and/or classical simulation. The exact project
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into areas such as AI-driven verification, predictive maintenance, and compliance assurance, aiming to enhance system reliability and safety. Situated within the esteemed IVHM Centre and supported by
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techniques with open-source autonomous driving software (for sim- ulation and testing) Applicants should fulfil the following requirements: a master’s degree in engineering sciences (preferably in computing
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advantages. We will provide the necessary hardware and software for the real-time control of the machine, but the candidate will be responsible for developing and implementing the control algorithms. A working
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Hardware-software co-simulation and benchmarking This PhD project is part of SDU microelectronic unit’s effort in neuromorphic chip design and collaborates with international partners working on spiking AI