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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance
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(approximately 10-15% of your time). You will be part of the Intelligent Systems group, led by Professor Mehdi Dastani, who will also be your supervisor together with Dr. Dragan Doder. Your qualities We
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intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of WASP
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methods to make them usable for transparent energy systems analyses. The collected data will be processed and semantically enriched using methods you develop before being transferred to a knowledge graph
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measuring stand for the collection of hyperspectral data on a test field Collection of imaging data and creation of a database Establishment of a data processing routine for pre-processing the hyperspectral
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and Computer Science AI/Machine Learning Nanotechnology/Devices (more...) Health Tech Microelectronics BioNanotechnology Material Science and Engineering Artificial Intelligence, Machine Learning and
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
for engineers. The aim is to move beyond data collection and develop intelligent methods that enable digital environments to understand and reason about real-world problems in safety-critical settings. To explore
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15.04.2025, Wissenschaftliches Personal The Lab for Artificial Intelligence in Medical Imaging (www.ai-med.de) is inviting applications for a fully funded PhD position in interpretable machine
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interconnected world, smart applications, and global business, necessitating the use of collaborative analytics, require the collection and processing of private information. In this PhD trajectory you will be
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Museums Trust. Ripon Museums Trust (RMT) is one of few independent museums holding significant policing collections. This positionality offers a rare opportunity to gain critical distance regarding