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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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interface, and all the way to quantum algorithms and applications. The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and quantum algorithms that solve life
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in e.g. qubit measurements and quantum error correction algorithms. The core responsibilities include modeling, simulating and designing components and chips for photonic and neutral atom quantum
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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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intelligent control and aerial robotics for navigation in uncertain environment. You will be mainly responsible: for implementation of machine-learning algorithms for unmanned aerial vehicles; validation
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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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sensing technologies (camera, Electromagnetic tracking system, FBG sensing) with continuum robotic systems and development of associated sensing and estimation algorithms 3D environment reconstruction based
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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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of these experiments. As part of this, we have developed new algorithms and a completely new web-based platform – EasyNMR - for performing such modelling/simulations. With this position, we seek to strengthen