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Field
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and hardware security assurance for embedded systems by combining advanced side-channel analysis, fault-injection techniques, AI- and machine-learning-assisted analysis, robustness evaluation, and
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: Advancing machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model
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decisive importance for lifetime performance modelling. The key challenges are the robust integration of a sensor system in the structure and the analysis of measured signals, which are typically strongly
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, and experiments on a robotic retinal surgery platform. Evaluate the accuracy, robustness, and real-time performance of the proposed navigation framework for autonomous retinal microsurgery. Expected
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: Advancing machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model
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-of-the-art models for robust and responsive food supply chains, you will investigate how disruptions such as droughts, floods, heatwaves, and other climate-related shocks might affect critical decisions
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carbon resources. Beyond polymer synthesis and recycling, you will investigate the use of these materials in durable and mechanically robust composites. This will allow you to connect fundamental molecular
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that capture ILC-specific morphology and biology while remaining robust to differences between hospitals, scanners, staining procedures and protocols. The researcher will investigate self-supervised and
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assurance for embedded systems by combining advanced side-channel analysis, fault-injection techniques, AI- and machine-learning-assisted analysis, robustness evaluation, and quantitative security assessment
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in trustworthy, explainable and reliable AI, including aspects such as transparency, robustness, interpretability and resilience of AI-based systems. Knowledge or demonstrated interest in anomaly