499 algorithm-development-"Multiple"-"Simons-Foundation" "Prof" PhD scholarships in United Kingdom
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Field
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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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4-Year PhD Studentship: Deciphering how domain organisation regulates heparan sulphate function Supervisors: Prof Cathy Merry, Prof. Kenton Arkill, Dr Andrew Hook Overview Glycosaminoglycans (GAGs
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-developing the principles (e.g. ethics) and methods for anonymising, processing and analysing sensitive data collected by a national charity’s 24/7 helpline for people experiencing or witnessing elder abuse
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sites returned 102,347 unique patient CCTA scan identifiers. 5,673 patients withdrew consent and 5,780 CCTA were multiple scans, leaving 90,553 patients who had received a CCTA during the study time
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Although the development of systems architectures and models has been an established practice for many years, the assessment of the quality of models has relied on expert judgement with
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High Mountain Asia (HMA), known as Asia’s Water Tower, is undergoing rapid economic development with growing populations in quickly developing countries. However, future development is hampered by
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sustainability goals whilst improving operational efficiency? This PhD studentship will involve developing machine learning models, creating virtual manufacturing replicas, and implementing optimisation algorithms
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how standard production practices impact biodegradability is essential for creating more sustainable textile alternatives. This research aims to develop a robust framework for measuring biodegradability
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bioinformatic skills to predict the evolution of rare diseases? FSHD is a rare neuromuscular disorder. No approved treatment is currently available. Slow and variable disease progression complicate trial design
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases