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conduct research on the theoretical foundations of mathematical optimization, as well as its applications to emerging challenges in machine learning and engineering. You will write and submit research
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Council (VR). The project is centered around inverse optimal control/inverse reinforcement learning, both for continuous-time and discrete-time systems. In particular, we are looking for a strong candidate
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. The permanent members of the algebraic geometry group at KTH are Mats Boij, Sandra Di Rocco, Kathlén Kohn, Georg Oberdieck, David Rydh and Roy Skjelnes. There is close collaboration with the algebraic topology
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Do you want to contribute to groundbreaking research in the intersection of battery systems and data-driven optimization? This is an exciting opportunity for a postdoctoral position at the Division
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learning methods for protein design Design of enzymes using computational models Identification and optimization of plastic-degrading enzymes Experimental expression, purification, and characterization
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monitoring for radiofrequency signals for various applications as anomaly detection, modulation classification, sensing, and adaptive spectrum optimization, we are now looking for a Postdoctoral Fellow with
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from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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of artificial intelligence (AI)-based spectral monitoring for radiofrequency signals for various applications as anomaly detection, modulation classification, sensing, and adaptive spectrum optimization, we
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Histological techniques, such as in situ hybridization and immunohistochemistry Confocal microscopy High-throughput screening approaches Development or optimization of molecular and experimental methods
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, topology, the mathematical foundations for data and AI, and mathematical statistics. A wide range of training opportunities for further qualification is provided. Up to 20% of the position may include