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on futuristic technologies in the field of machine learning and computer vision. Hence, we investigate and develop an innovative computation-in-memory (CIM) solution for artificial intelligence accelerator design
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. The performance of the developed methods will be evaluated using real operating data. In addition, it will be investigated how reliability and safety conditions can be taken into account. This is particularly
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trajectory planning in safety-critical scenarios. For this purpose, we focus on modeling and quantifying risks in order to subsequently incorporate them into trajectory planning. The goal is to enable safe and
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Science. The PhD positions will be at the intersection of Data Science and Social Sciences and will focus on topics such as Explainable & Fair AI, AI Auditing, AI Alignment, and AI Safety in general. We