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, fermentation, and functional foods. Hands-on experience in identification, selection, and non-GMO optimization of bacterial strains. Practical experience with analytical equipment and microfluidics platforms
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dietary intake estimates. This work will involve the use and optimization of advanced analytical tandem mass spectrometry methods, assessment of vitamin D bioaccessibility using an in vitro model, and
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program. Strong interest in microbiology, fermentation, and functional foods. Hands-on experience in identification, selection, and non-GMO optimization of bacterial strains. Practical experience with
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engineering, or similar. Solid mathematical and analytical skills, including signal processing and optimization. Knowledge about classical and/or quantum data communication, including for instance error
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algorithmic solution development. The group focuses particularly on automated decision-making in autonomous cyber-physical systems, combining mathematical optimization, machine learning, and decision theory
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the shift from the robust architecture of radio-TV transmitters and receivers to the far more complex and fragile structure of ‘over-the-top’ (IP-based) media delivery. The project will model optimal
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framework offering optimal inspection and maintenance decision support. Explore additively manufactured structural concepts, including performance trade-offs for lightweight, fatigue- and corrosion-resistant
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optimization and enable automated diagnosis of performance-limiting factors and suggest optimization strategies. The project will be part of the DFF Sapere Aude project, and research stays abroad are part of
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assessment. Design and train reinforcement learning agents to optimize operational safety. Build and validate dynamic Bayesian network models integrating empirical and synthetic data. Conduct scenario-based
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alerts, facilitating optimized maintenance decisions and reducing unplanned downtimes. The framework will be validated through close collaboration with industry partners, incorporating actual operational