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, Position 2 on adaptive policies, and both will work jointly to integrate the two approaches into a single RL algorithm. While the work is mainly methodological and theoretically focused, our Aalto robot lab
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work jointly to integrate the two approaches into a single RL algorithm. While the work is mainly methodological and theoretically focused, our Aalto robot lab offers the possibility to evaluate the
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models of analog and RF circuits in Python Validate the developed models against circuit simulations and measurements Perform hardware-algorithm co-design for AI-driven 6G transmitters Publish and
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-standard tools such as Matlab Simulink to connect with existing control systems and support SIL/MIL simulation, and the resulting algorithm must run efficiently within the CPU constraints of an embedded
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RF circuits in Python Validate the developed models against circuit simulations and measurements Perform hardware-algorithm co-design for AI-driven 6G transmitters Publish and present your results at
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whole fleet can act as one Virtual Power Plant. Read more about the project and other participants here: https://aegis-dn.eu/ Your role: You will be working on “End-to-End Energy Modeling for
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Future robots must perceive, predict, communicate, and decide reliably in complex, human–robot shared environments. The Mobile Robotics ( https://www.aalto.fi/en/department-of-electrical-engineering
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fleet can act as one Virtual Power Plant. Read more about the project and other participants here: https://aegis-dn.eu/ Your role: You will be working on “End-to-End Energy Modeling for Distributed AI
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, and decide reliably in complex, human–robot shared environments. The Mobile Robotics ( https://www.aalto.fi/en/department-of-electrical-engineering-and-automation/mobile-robotics ) and Intelligent
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, computational science, or closely related). Relevant coursework (examples): Computational physics/scientific computing and numerical methods for PDEs High‑performance computing (parallel distributed