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increasing relevance today due to its ability to bridge the physical, digital, and social domains. CPSS are integral to the modern world, shaping the development of intelligent systems that respond dynamically
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for Encrypted IoT Traffic Please note, this is open to home students only. PhD Studentship:cyberQuarter funded. The Studentship is available for an October 2025 start. A PhD studentship that comprises tax-free
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, adaptive control strategies, and hybrid energy storage solutions to address key challenges in self-powered systems under dynamic environmental conditions by: Develop machine learning or heuristic-based
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, embedded intelligence, and adaptive cyber-physical systems that operate safely under uncertainty and dynamic conditions. This PhD at Cranfield University explores the development of resilient, AI-enabled
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failure due to high-cycle fatigue, reducing the efficiency and safety of the gas-turbine engines. The development of robust damper devices that reduce the vibration levels is of paramount importance
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multidisciplinary research team within the School of Electrical, Electronic and Mechanical Engineering. SMG is known for its work in computational mechanics, fatigue, fracture, and advanced materials modeling
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of tomorrow and creating novel solutions to major global challenges. Our community is made up of 13 000 students, 400 professors and close to 4 500 other faculty and staff working on our dynamic campus in Espoo
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candidate will conduct fundamental research aimed at understanding cell shape dynamics and the cross -talk between cell shape and cell state during epithelial-to-mesenchymal transition (EMT). The aim
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cybersecurity Please note, this is open to home students only. PhD Studentship: CyberQuarter. The Studentship is available for an October 2025 start. A PhD studentship that comprises tax-free stipend of £20,870
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propulsion forces, uncovering the new fundamental principles that govern their movement. The physics of swimming on these small length scales is fundamentally different to that when we swim. By characterizing