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) Willingness to work in a highly interdisciplinary context and develop a set of interdisciplinary methods (i.e., dealing with both qualitative and quantitative data) Interest in engaging with stakeholders active
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to develop innovative methods and actionable tools for detecting, analyzing, and preventing vulnerabilities in supply chain systems, leveraging state-of-the-art AI and ML techniques to improve overall security
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Analyze and assess risks of de-anonymization, including researching current de-anonymization strategies Investigate synthetic data generation methods and their utility Deploying and benchmarking the above
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the following activities: Conduct highly innovative research in the intersection of cybersecurity and safety-critical systems, in dependability methods and solutions and in architectures and systems that support