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extended from cloud solutions (such as OpenLLMetry), the research question is how to identify anomalies in collected information that can come from multiple AI services either invoked manually by users or by
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. The research project of the PhD student will thus focus on aggregating heterogeneous OSINT (Open-Source Intelligence) sources and aggregate retrieved data with cyber-risks indicators of the targeted environment
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languages (C,C++, Python) Knowledge of offensive security Good scientific writing Involvement in the preparation of articles for publication in scientific journal(s) Data analysis skills Knowledge of advanced
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, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and
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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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synthetic fuel reactors. Tasks include gas handling, system diagnostics, thermal integration, and performance evaluation under variable power inputs. Data Analysis and Machine Learning: Collect and process
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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, or related discipline, or a similar degree with an equivalent academic level. You will be expected to have: Excellent written and oral communication skills Research and data analysis Excellent analytical and
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, Internet of Things, Systems-of-Systems automation, Machine Learning, Deep Learning, Data Science, Electronic systems design, and sensor systems. Cyber-Physical Systems (CPS) focuses on integrated software