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rapidly evolving areas such as autonomous systems, data-driven modeling, learning-based control, optimization, complex networks, and sensor fusion. Research at the division is characterized by close
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expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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algorithms. Our research integrates expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems
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- Markovian Processes - Network Based Localisation / Radio based connectivity - Adaptive bandwidth - Mesh networking - Wireless Sensor Networks - Edge Computing - Time Delayed Systems - Adaptive Queuing
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net radiation, and because snowmelt and evapotranspiration (ET) of meltwater are sinks for latent heat. Growing season water inputs in these environments originate from both rain and meltwater, but
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teaching in key and rapidly evolving areas such as autonomous systems, data-driven modeling, learning-based control, optimization, complex networks, and sensor fusion. Research at the division is
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creative and stimulating environment with the opportunity to network with both the business community and international contacts. Read more about our benefits and what it is like to work at SLU at https
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consists of a diverse set of people from different nationalities, backgrounds, and fields. As a PhD student working with us, you receive the benefits of support in career development, networking
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Engineering and will become part of the national graduate school FOFOS – Research School for the Transformation of the Public Sector (https://www.mdu.se/forskning/forskarskolor/forskarskolan-fofos ). FOFOS is
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of a diverse set of people from different nationalities, backgrounds, and fields. As a PhD student working with us, you receive the benefits of support in career development, networking, administrative