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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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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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. Supervision: Dr. Rafael Guedez, Prof. Björn Laumert and Dr. Silvia Trevisan are proposed to supervise the doctoral student. Decisions are made on admission What we offer The possibility to study in a dynamic
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significant role in learning in AI by enabling cognitive agents to acquire actively knowledge and skills through interaction with their surrounding environment. Embodied AI requires tools, algorithms, and