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This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project
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the development of trustworthy and deployable medical AI systems.
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funded by the university with excellent opportunities for both research and career development. The newly established research group in Particle and Fiber Technology for bio-based Materials, led by Prof
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University Rose-ringed parakeet vocal behaviour and social interactions across the Netherlands Michelle Spierings Universiteit Leiden Symposium Social Evolution – Dynamics of Sociality Carsten de Dreu
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crucial insights. In this project, you will contribute to the development of AI-driven methodologies for experimental fluid mechanics , focusing on: Designing multi-fidelity neural networks for adaptive
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strong support for personal and professional development. The PhD students will be enrolled in the ETH Zürich doctoral program. The position is available from April 1st 2026 or upon agreement. We live a
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. Methodology The PhD will be divided into 3 work packages (WP): WP1 - Digital Twin Development: This WP focuses on building physics-informed digital twins for high-impact use cases: Smart Grids (simulating load
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for contraceptives. To this end, we bring together scientists from the University of Münster, University Hospital Münster, and the University of Hamburg. Our goal is to advance the development of innovative, non
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academic development. You'll have freedom to explore ideas within the project scope, supported throughout by your supervisor, Dr. Martin Haase. This PhD offers strong preparation for a career in academia or
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reproduction, novel contraceptive development, and the conservation of Australian fauna. The project is laboratory based and expected to be undertaken full-time, onsite at the Callaghan campus. PhD Scholarship