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Field
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identify those with the highest potential for early adoption in space engineering; translate theoretical advances into algorithmic innovations, design principles and prototype tools that can be integrated
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to operate in a scalable and decentralized manner while achieving obstacle avoidance using onboard sensing and adapting to changes in dynamic environments. In parallel to the theoretical and algorithmic
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, development and implementation of digital signal processing algorithms and data processing strategies for microwave radiometers; conducting laboratory activities to validate architectural concepts, operating
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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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different incentives, mechanisms and regulatory scenarios, evaluating their performance with respect to different objectives and their trade-offs. Developing decentralized and bi-level algorithms to help
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optimization and resource allocation schemes and algorithms for link and network optimization with hybrid fibre-FSO-RF communications. You will further augment software defined networking controllers
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subjective assessment. Design and implement machine learning algorithms for real-time prediction of occupant thermal comfort. Analyse physiological signals including skin temperature, skin conductance, heart
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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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and implement machine learning algorithms for real-time prediction of occupant thermal comfort. Analyse physiological signals including skin temperature, skin conductance, heart rate, and wearable
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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