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collaborate closely with hardware designers and industrial partners, benefiting from their complementary expertise and datasets. The position is embedded in the CAES chair of the EEMCS faculty, which offers a
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and hardware. Expect a dynamic, cross-border innovation ecosystem where your contributions directly influence the future of sustainable transport. Information and application Are you interested in
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designs of AI systems should be assessed during the design phase. Data flow diagrams are already used in NOLAI, and capture all the processing, storing and transmission of data: elements in
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develop methods to steer developments of large AI systems in such a way that they are environmentally sustainable. To this end, different designs of AI systems should be assessed during the design phase
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way to enhance radar perception without requiring hardware modifications. You will develop AI models that generate high-resolution radar data from cameras, LiDAR, or low-resolution radar inputs