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-Interaction” within the WASP project, led by Assoc. Prof. Zoe Falomir. The position is full-time for two years, starting in spring 2026, or as agreed. Department of Computing Science For our department
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, or equivalent, with excellent knowledge of digital communications and signal processing. High grades in the core courses are required. Skills in mathematical analysis, modeling, and network algorithms
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through interaction with their surrounding environment. Embodied AI requires tools, algorithms, and techniques to cope with real-world challenges including but not limited to uncertainty, physical
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their ability to: independently pursue his or her work collaborate with others, have a professional approach and analyze and work with complex issues. Experience in machine learning, algorithmic theory, or code
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absorption/fluorescence and scattering experiments at X-ray free electron lasers. Your focus will be to derive new algorithms for interpretation of the scattering data by introducing chemical force-fields via
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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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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