76 phd-position-computer-science-"IMPRS-ML"-"IMPRS-ML" positions at Cranfield University
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sanitation globally. This position offers exceptional opportunities for international engagement through coordination with global partners, with potential travel for field trials and technology validation
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conduct interdisciplinary research combining software engineering, artificial intelligence, IoT development, and human-computer interaction to create intelligent software systems that serve both technical
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Smart sanitation technology represents a critical intersection of automation engineering, embedded systems, and global health innovation. With 3.6 billion people worldwide lacking access to safely
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Design and Manufacturing Engineering to Tackle Global Sanitation Challenges - MSc by Research or PhD
Design and manufacturing engineering represents the critical bridge between innovative concepts and real-world implementation, particularly in global sanitation technology where products must be
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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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This self-funded PhD opportunity focuses on assured multi-domain positioning, navigation, and timing (PNT), integrating data from space-based, terrestrial and platform-based sources of navigation
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Join us for this exciting self-funded PhD studentship on " Development of Sustainable and Cost-Effective Coatings to Mitigate Battery Thermal Runaway Propagation" in collaboration with
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PhD research project in Zero Emission Technologies related to LH2 for civil aviation. The Centre for Propulsion and Thermal Power Engineering is one of the largest research and education activities
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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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disruptive aircraft configurations involves combining advanced engineering practices, including computing power, sensing, AI/ML, and system-level engineering. Comprehensive verification and validation