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We are looking for a Research Associate to contribute to the development of next-generation battery management systems (BMS). The position is hosted by the Automatic Control group at the Division
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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
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system complexity. Your work will include: Developing modular, efficient, and transparent control algorithms. Combining model predictive control with learning-based motion prediction under uncertainty
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modeling, and algorithm development, with experimental validation using Chalmers' advanced multi-antenna testbed. The overall objective is to contribute to the development of energy-efficient and high
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intelligence in general. The focus is broadly upon the development of numerically stable and efficient computational algorithms, their implementation and testing with computer programs, both in simulation as
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of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial intelligence in general. The focus is broadly upon the development
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, design and characterization of quantum processors Development and optimization of nano-fabrication processes for large-scale devices Development of optimal control techniches to achieve fast and high
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on building the next generation of quantum processors based on superconducting circuits. To achieve this ambitiuous goal, we have a variety of projects related to: Development and optimization of nano
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before the application deadline* Demonstrate strong mathematical skills, particularly in optimization and algorithm development Have a publication record in peer-reviewed journals (e.g., IEEE Transactions
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Join us in developing innovative flow control systems to enhance wind-assisted ship propulsion and support sustainable maritime technology! About us The Department of Mechanics and Maritime Sciences