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investigate and develop innovative memory solutions in advanced CMOS technologies such as FDSOI. The development of integrated circuits also plays an important role in making these networked devices and their
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This self-funded PhD research project aims to develop smart sensors based on low-frequency resonance accelerometers for condition monitoring of ultra-speed bearings. The developed smart sensors will
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investigate and develop innovative memory solutions in advanced CMOS technologies such as FDSOI. The development of integrated circuits also plays an important role in making these networked devices and their
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investigate and develop innovative memory solutions in advanced CMOS technologies such as FDSOI. The development of integrated circuits also plays an important role in making these networked devices and their
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investigate and develop innovative memory solutions in advanced CMOS technologies such as FDSOI. The development of integrated circuits also plays an important role in making these networked devices and their
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of associated ecosystems under events of wastewater discharge, industrial discharge, and urban runoff. In the Muncipality of Ålesund in Norway, a network of sensors has been installed in a drinking water source
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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developing and deploying an ocean‑monitoring system for offshore installations. The research will integrate optical and acoustic sensors, autonomous data collection, and advanced perception methods to track
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PhD Studentship available in the EPSRC Centre for Doctoral Training in Robotics and AI for Net Zero (RAINZ) This studentship is offered by the EPSRC Centre for Doctoral Training in Robotics and
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(a) networked multi-agent human-robotic systems that work collaboratively in a well-coordinated and safe manner, (b) computational design and digital manufacturing of components, (c) design of