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ecosystem health in the northern Scandinavian mountain ranges. The project will include fieldwork in the mountains near Abisko in northern Sweden, where eddy covariance sensors will be used to measure ET in
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-edge academic insight with real-world robotics applications. The PhD project will focus on the design of advanced control and decision-making algorithms to enhance the intelligence, autonomy, and
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artificial intelligence and control systems. In this project, you will design new algorithms for semantic communication between the cloud and autonomous systems—technology that can transform how robots, drones
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. Lab Research: • AI-Driven Algorithms & Software: Develop deep leering/machine learning/statistical based algorithms to elucidate lncRNAs, fusion transcripts, RNA modifications, and circular RNAs in
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the development of methods and models refinements, analyses, and optimizations for scale-grid TES integration and operation planning algorithm. RESTORATIVE consists of 17 PhD students at 7 universities and 4
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capable of leveraging signals from terrestrial base stations, non-terrestrial networks such as LEO satellite, and complementary on-board sensors. Specifically, it will: To design reconfigurable airborne
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pooling coordination schemes for CF-based 6G RANs. His/Her work will adress objectives like: (i) develop low-complexity ML algorithms for efficient multi-objective network optimization, radio resources
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with sufficient accuracy using fast parametric algorithms and machine learning (ML) models instead of time-consuming simulations to evaluate scenarios for improving the user experience along cycling and
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of algorithmic systems. The research will investigate how clinicians interact with automated and machine learning–based decision-support systems, with a particular focus on cognitive workload, trust, situational
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sensors, instruments, and data analytics for such applications. The position responsibilities also include giving periodic progress reports via slide decks and written documents, working as part of a multi