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Field
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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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Engineering, Computer Science or related + 2 years of experience researching multi-armed bandit problems and developing and analyzing Bayesian optimization and reinforcement learning algorithms + at least 3
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econometric analysis and preparing results tables, managing large data sets, handling spatial data, applying machine learning algorithms, conducting computationally intensive statistical analyses, summarizing
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the internal computations and circuits within large models. Can we reverse-engineer the "algorithms" that a neural network has learned? Value Alignment & AI Ethics: How do we formally define and embed complex
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algorithms proficiency in both general-purpose programming (e.g., Python) and scientific computing, with a preference for experience in Julia Experience in writing up research work for publication Highly
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the research in combining AI techniques with formal methods techniques (especially program synthesis) to improve the explainability and robustness of AI models Participating in co-operation with Continental’s
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manufacturing, mechatronics, innovative design, nanotechnology, and biomedical and computational applications. Key Responsibilities: The research fellow will be leading the development of AI-based decision-making
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and Applications of Algorithms” at the Faculty of Computer Science. The position is limited to six months and is planned to be filled from 01.10.2025. Your future tasks: Participation in research
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research for digital security and is a pioneer in developing highly innovative concepts, algorithms and systems for anomaly detection, cyber threat intelligence, penetration testing and cryptography. Through
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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing