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data and IT infrastructure. Combination of different algorithms to test multimodal predictive modelling. Compilation and presentation of data orally at seminars and conferences, as well as independent
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, modulation classification, sensing, and adaptive spectrum optimization in diverse operational environments. Your work will focus on modeling and algorithmic aspects related to the development of highly
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each year. You can find more information about us on the Department of Information Technology website. At the Division of Systems and Control in the Department of Information Technology, we develop both
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will be as a researcher in a two-year project carried out in close collaboration with our industry partner. The goal is to develop methods for an ML-based decision support system for monitoring and fault
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-year project carried out in close collaboration with our industry partner. The goal is to develop methods for an ML-based decision support system for monitoring and fault diagnosis of gas turbines
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algorithmic aspects related to the development of highly accurate, efficient, and robust AI models capable of operating effectively within complex and dynamic radiofrequency spectral landscapes, accounting
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to make a difference. Do you want to be involved and contribute to our development? Together, we can create a sustainable future through knowledge and innovation. We believe that knowledge and new
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on methodological development in cryo-electron microscopy (cryo-EM), particularly in image reconstruction and 3D volumetric analysis of macromolecular structures. Rather than aiming to incrementally optimize existing
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application! Work assignments This position focuses on the development of theoretically grounded and practically scalable decentralized learning algorithms under realistic system constraints, including
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Sapere Aude – dare to know – is our motto. Our students and employees develop important knowledge that enrich both the individual and the community. Our academic environment is characterised by