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Field
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systems—commonly referred to as neuromorphic computing—holds the potential to create highly intelligent machines capable of supporting a wide range of everyday applications, from autonomous vehicles
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the following traits: Educational background: A master’s degree in computer science/artificial intelligence with a solid grounding in optical and spectroscopic instrumentation, such as hyperspectral, NIR, and
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. Focusing on adaptive intelligence, which blends human creativity and machine intelligence, the project will develop Multi-Intelligence Agents (MIAs) to facilitate the seamless integration of social factors
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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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PhD degrees in computer science, a BSc in artificial intelligence, and an MSc degree in data science. The project is supervised by Stelios Tsampas (stelios@imada.sdu.dk ) and Marco Peressotti
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data to answer relevant questions and solve real-world problems. It brings together fundamental, methodologically driven research in optimization, machine learning, and artificial intelligence with
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PhD Studentship: Artificial Intelligence for Building Performance – Optimising Low-Pressure Airtightness Testing Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo
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Master’s degree in Data Science, Artificial Intelligence, Computational Linguistics, Computer Science. Has excellent academic writing and oral skills in English. Has experience with large language models
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programs – specifically MS Office (Word, Excel, and PowerPoint). Maintain excellent lab notes and records. Demonstrated ability to work cohesively in a team and display initiative in anticipating and
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at Nottingham https://www.nottingham.ac.uk/coatings/ is an international reference for all Thermal Barrier Coating activities. This PhD programme, in partnership with Rolls-Royce, will address key challenges