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of higher education in engineering or fields related to agriculture Enrolled in a PhD programme (Doctoral studies) Skills / Qualifications Background in smart agriculture, environmental monitoring, IoT
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Engineering and Mechatronics. The Proposed PhD thesis topic: “Intelligent Diagnostics of Electrical Machines through AI-Enabled IoT Systems: Design of Custom Embedded Hardware and Protocol-Aware Architectures
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: Enhancing full-scale power-speed assessment reliability by using IoT and big data management Summary This PhD research focuses on uncertainty challenges caused by various disturbances (wind, wave, current
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digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design
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, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks
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to contribute to climate-conscious innovation across sectors such as autonomous mobility, IoT, and space technologies, where energy resilience is a key differentiator.
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, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models
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, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
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) Position C Powering data-driven sustainability assessment tasks in agri-food systems with IoT-data Datlakes and Large Language Models. Aarhus University (DK) & Université Libre Bruxelles (BE) Position D
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sustainability assessment tasks in agri-food systems with IoT-data Data lakes and Large Language Models. PhD grantors: Aarhus University (DK) & Université Libre Bruxelles (BE); keywords: data lakes, LLMs