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Field
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and algorithmic framework to assess and improve the resilience of FL-enabled autonomous systems under such heterogeneity, explicitly incorporating the human in the loop. The project will draw
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structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We will consider techniques like flow matching, and use ideas from optimal
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primarily on the development, validation, and implementation of the Psychological Referral Optimization algorithm (PRO). PRO is a brief digital e-screening tool designed to support early identification, risk
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novel algorithms, aiming for theoretical guarantees when working with structured and unstructured data. Pursue and complete a PhD thesis within the appointed 4-year duration. Join the Vienna Doctoral
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advanced algorithms for solving complex optimization problems. You will work with real-world case studies to design future-proof supply chain networks for key agricultural products in vulnerable regions
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of artificial intelligence and consumer behavior. • Designing, developing, and evaluating artificial intelligence (AI)-based techniques and algorithms related to consumer behavior and manipulative online
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: Transparency. As part of this doctoral project, you will develop novel knowledge representation techniques, algorithms for human-in-the-loop optimization, and interactive tools that combine graphical and natural
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the nonlinear dynamics of these networks using theory and numerical simulations. - Design and perform table-top robotic experiments that implement your learning algorithms in unpredictable environments. Who
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will be carried out on a nuclear reactor simulator, with the possibility of validating results on a physical non-nuclear test system. You will design control algorithms that handle the full range
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mechanisms to protect sensitive information, trusted operations, and critical functionality. While cryptographic algorithms and software-level protections may be theoretically secure, their physical