772 algorithm-development-"Multiple"-"Simons-Foundation" "Prof" Fellowship positions in United Kingdom
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-holomorphic Hilbert Modular Forms”. The central aim of the project is to develop explicit algorithms for computing with non-holomorphic Hilbert Modular Forms and using these algorithms together with theoretical
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, the latest facilities and access to a variety of staff development opportunities. You are invited to contact Professor Bakr Bahaj (a.s.bahaj@soton.ac.uk ) or Prof Patrick James (paj1@soton.ac.uk ) for further
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the supervision of Prof Amedeo Chiribiri within the Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Sciences, King’s College London. About The Role Applicants should be medically
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have developed some of the most remarkable morphological systems on the planet, where simultaneous manipulation of multiple phonological features (vowel length, vowel height, tone, phonation type
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have developed some of the most remarkable morphological systems on the planet, where simultaneous manipulation of multiple phonological features (vowel length, vowel height, tone, phonation type
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the climate crisis while also demonstrating a strong background in communicating evidence and insights to multiple stakeholders. Please note that this post may be suitable for sponsorship under the Skilled
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institutions, and leading industry partners. The successful candidate will contribute to the delivery of high-impact research projects involving AI algorithm evaluation and image data analysis. You will play a
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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing
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highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to predict the impact of mutations on genes in the avian flu virus and the viral host which
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binding pockets. About the role We are seeking a highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to identify domain functional families