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Design and Manufacturing Engineering to Tackle Global Sanitation Challenges - MSc by Research or PhD
manufacturing frameworks for advanced sanitation systems, focusing on optimizing both product design and production processes through advanced CAD modeling, 3D printing technologies, and manufacturing
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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This PhD opportunity at Cranfield University invites candidates to explore the integration of AI into certification and lifecycle monitoring processes for safety-critical systems. The project delves
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resources planning. Water company resources planning is a mature process incorporating climate change and environmental protection with robust options development and clear governance. Various initiatives
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enhancing electronic performance and resilience using AI techniques. The research aims to develop intelligent, adaptive, and high-performance electronic architectures that support real-time processing, energy
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at leading international conferences and publish in top-tier journals. The successful candidate will gain advanced expertise in multi-sensor fusion, signal processing, machine learning, and positioning
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the development of specialized hardware architectures capable of efficient, real-time processing. Embedded AI hardware architectures, including neuromorphic processors and low-power AI accelerators
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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
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projects, international collaborations, and experimental campaigns using software-defined radios and UAV operation platforms. The project offers mix of theoretical development, simulation-based research, and
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realistic degradation from corrosion processes. The simulations will be integrated with mesoscale experimental to evaluate the constitutive response of smooth specimens degraded by corrosion. Given