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experimentation. The PhD student will develop models and algorithms for the joint design of sensing, communication, inference, and action, and is expected to contribute to a real robotic platform integrating
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. The tasks include battery cell characterization and modelling based on laboratory tests, and development of algorithms for estimating the charge level, health, and power capability which includes robustness
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and corrective feedback. You will apply advanced algorithms for machine learning, multimodal biosignal processing, and human-state inference, working with shared-control strategies and electrotactile
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, outreach and knowledge brokering activities of the Algorithms, Data and Democracy project (ADD) of which the IPA project is part (see www.algoritmer.org ). teach, supervise and examine students in Master of
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dynamics, control algorithms and sensor integration can be designed as a coherent system to improve speed, range, maneuverability, response time and operational robustness while also having underwater
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analytical skills. Knowledge about statistical machine learning, robotic perception, multimodal AI algorithms. Proven experience with reinforcement learning algorithms and implementations. Experience in
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spectrum of topics, ranging from fundamental vision algorithms and deep learning methods to applied research projects carried out in close collaboration with industrial and public partners. Read more on
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experimental validation of control strategies for the developed systems. This includes the development of advanced control algorithms capable of handling varying operating conditions, ensuring system stability
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closely related field, with a strong background in AI/ML technologies, including algorithm development, optimization, and data-driven modeling. Candidates are expected to demonstrate research leadership
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explore applications of quantum resources in a network setting. Among the research topics are quantum cryptographic algorithms and quantum error-correction. How to apply Your application must include