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learning, optimization algorithms, and interoperability frameworks for optimal energy management across Europe. KTH leads technological landscape analysis, multi-energy investment planning tool development
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develop new communication theory and signal processing algorithms. The goal will be to develop theory, algorithms, and network architectural concepts to deliver ubiquitous network services across the globe
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the mathematical foundations of these fields, e.g., designing innovative algorithms and control strategies, as well as the development of technical solutions to adapt these new methods to applications in the areas
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embodied cognitive agents can learn to solve complex problems and adapt in dynamic real-world environments. This research direction demands developing novel techniques and algorithms that can enable
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to support short- and long-term decision-making, developing new integrated designs and operation of complex industrial sites. The project is in collaboration with DTU Construct and research stays are planned
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mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. Experience in applying or developing machine learning
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prominent approach to AI, with impressive performance in many application domains, including materials discovery. This development has a huge potential for societal impact, with applications in renewable
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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department
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in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several
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modular, scalable, and transparent control algorithms suitable for real-time implementation across different vehicle platforms. - Contribute to theoretical developments in stochastic model predictive