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machine learning, spatial audio and audio-visual AI into groundbreaking creative technology. About you We seek a talented Research Fellow to investigate generative audio AI technology for production
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, accumulated deformations, and their impact on structural performance, particularly for compression members. Develop data-driven reusability assessment platforms integrating NDT data, machine learning models
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at FHEQ level 7 (Master’s level) across AI foundations and machine learning to learners from varied academic and professional backgrounds. Ability to develop and deliver high quality and innovative teaching
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and research grants (appropriate to career stage) Expertise in advanced quantitative and/or qualitative research methods, including AI or machine-learning based approaches. Ability to design, deliver
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communities. These facilities create a unique offering in higher education for our students to gain valuable practice learning experience onsite, to support local and regional NHS partners, and provide a data
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and machine learning systems led by Prof Christopher Summerfield. The post-holder will have responsibility for carrying out rigorous and impactful research into human-AI interaction and alignment, with
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The postdoctoral researcher will lead the development of computational methods for aligning cortical organisation across species using transcriptomic and anatomical data combined with modern machine
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imaging, physiological measurement, machine learning, and high-performance computational modelling. You will work with cardiology, cardiac electrophysiology, imaging, and biomedical engineering teams
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own and within your team to provide a first-class cleaning service for the College. Applicants must have the ability to work on their own in student & learning environment, be conscientious, hardworking
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. You will then develop a predictive Machine Learning tool to support engineers in incorporating vegetated systems into design stage decision making. Finally, you will apply Life Cycle Analysis