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stability theory, modeling & identification, optimal control, certifiably safe & robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven
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and power converters. Our work spans from fundamental modelling and analysis to advanced control design and system optimization. Our specialty is developing embedded control, estimation, and
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the opportunity to visit various partners in the network. The goal is to explore new synergies between natural language–based human-AI interaction, nature-inspired optimization and exploration
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optimization of single-phase LCL filter inductors taking into account dynamic hysteresis models for different magnetic core materials. Supervisor: Prof. Paavo Rasilo (Electromechanics) Secondments: Université
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processed by advanced and sustainable manufacturing, integrated in the circular economy. The starting point in modern production at M2P is digital data, generated and optimized. Research methods encompass
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(land, aerial, marine, or hybrid) Distributed decision-making, task allocation, and worksite optimization under uncertainty Energy-aware and resource-efficient collaboration strategies for fleets
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, human-centric systems, and technology deployment. Your research may focus on any of the following themes or a combination thereof: -Design, optimization, implementation, ramp up, and operation of
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skills and experience in written, spoken, and collaborative work in English. What we offer: A career path optimized for transition to industry. You will be affiliated with the dynamic Aalto Scientific
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leverage the theory of estimating functions to create optimal inference algorithms for the proposed loss functions based on its underlying Riemannian geometry, as well as for those previously introduced in
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technologies to facilitate efficient optimization of the enzymes and products. The applications of this research span enzyme technologies to functional biomaterials. Scientific environment The Department