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possible for up to 1 day/week. You will join an interdisciplinary team of researchers spanning imaging science, machine learning, genetics, and population health, working closely with collaborators
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well as companies and governmental organisations . They will contribute to the activities of the wider machine learning and data science research group and write up the results of their work, with co-authors
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collaborate with other technical groups working on the design. The successful candidate will also have opportunity to conduct experiments and machine development activities on the existing accelerators. The key
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: Experience implementing Quantum Monte Carlo methods. Experience applying Machine Learning methods to scientific problems. About the School The School of Physical and Chemical Sciences is one of the UK’s elite
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. About the Role The post is funded for 3 years and is based in the Big Data Institute, Old Road Campus. You will join an interdisciplinary team of researchers spanning imaging science, machine learning
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manufacturer. Based on our publication (ACS Appl Nano Matter 2022, 10.1021/acsanm.2c03406) and our ongoing collaborative work, we have developed a new chemical assay coupled with a machine learning algorithm to
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conferences in machine learning, statistics, and communications. Presenting research findings at project meetings, workshops, and international conferences. Supporting the supervision of PhD students and
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and machine learning. Topics of interest in this area include, but are not limited to: natural language processing, large language models, graph learning, prompt engineering, knowledge graphs, knowledge
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and learning adaptation to uncertainty. You will use fMRI and neurostimulatory techniques (ultrasound neurostimulation and/or transcranial magnetic stimulation) to test the causal role of targeted
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the scientific investigation of artworks and historical objects. The project aims to advance the mathematical foundations of imaging and machine learning while directly supporting research in art history