31 algorithm-"Multiple"-"Prof"-"Simons-Foundation"-"Embry-Riddle-Aeronautical-University" positions in United Kingdom
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-resource settings. This project aims to achieve several objectives, including the development of a new AI-algorithm and a paired dataset for comparing how different imaging techniques influence
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; https://github.com/CogStack/MedCAT ) projects alongside any deployment specific enhancements and specialisations. This work will include contributing to our clinical NLP tools, algorithms and interfaces
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physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals
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development, human-computer interaction, data analytics, user experience design, remote monitoring systems, energy optimization algorithms, and environmental impact modeling. Human-centric AI-driven sanitation
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independent higher education provider, offering flexible and inclusive learning across multiple London campuses. We are student focused, digitally forward, and committed to academic excellence reflected in our
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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. An optimisation tool has been developed that uses a genetic algorithm to optimise the location of BGI taking surface water flood risk reduction and the cost of different interventions into consideration. This PhD
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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. The posts will involve working across multiple project grants aiming to evaluate the use of wearable technology in laboratory and real-world settings to quantify digital mobility outcomes in ageing and