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to next-generation 2D gas sensors. You will manage large-scale simulations run on world-class supercomputing facilities alongside AI algorithms and data analytics tools, and share your results with
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user studies, develop novel algorithms, build immersive/augmented realities, and validate your solutions in real-world settings. This PhD is ideal for candidates interested in one or more of the
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user studies, develop novel algorithms, build immersive/augmented realities, and validate your solutions in real-world settings. This PhD is ideal for candidates interested in one or more of the
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with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of WASP is excellent research and competence in artificial
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operation will be studied. From a methodological perspective, the above research challenges will be tackled through a mix of theory, algorithm design, and analysis of experimental data, partly collected by
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;Knowledge in the collection, processing, and analysis of data obtained from physical activity and exercise monitoring technologies (e.g., wearables, sensors, or equivalent systems);Knowledge of exercise
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commissioning and adaptive control. The PhD candidate will develop methods for the ongoing, automated adjustment of controllers, sensors, actuators, and associated control hardware. Rather than one-time
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translate abstract democratic, organisational, and societal values such as algorithmic fairness, transparency, explainability (XAI) into rigorous, quantifiable engineering metrics without sacrificing
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of a detailed set of models that characterize the capabilities and limitations of each type of robot in the fleet, including kinematic models, sensor capabilities, communication systems, and command and
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democratic, organisational, and societal values such as algorithmic fairness, transparency, explainability (XAI) into rigorous, quantifiable engineering metrics without sacrificing the general utility of said