422 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" Fellowship research jobs in United Kingdom
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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the design, development, deployment and evaluation of NeoShield’s applied machine-learning systems, the machine-learning-driven Clinical Decision Support Algorithm for neonatal sepsis and the real-time ward
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second in the UK for research power and first in England. About the role The project will be carried out at the Department of Computer Science, in the Machine Intelligence Lab (https
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biology, engineering, biophysics, computer science) and experience in 3D imaging of brain tissue, image segmentation, and handling large datasets. You are comfortable with machine learning and image
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Overview of the Role Are you experienced in machine learning and looking to apply your skills to solve new challenges and reduce disaster risk? Do you want to further your career in one of the UKs
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’. The role-holder will work closely with medicinal chemists at University of Oxford and pharmacologists at University of Glasgow, applying virtual screening, machine learning, AI-driven generative chemistry
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Offer Description We are seeking to appoint a Postdoctoral Researcher for a three-year position in machine learning emulators of ice-ocean processes. The role is part of PRECISE: Prediction of Climate
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or machine learning. Excellent programming skills in Python and deep learning frameworks A collaborative mindset and interest in socially impactful research. Experience with sign language data, multimodal
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to learn from others is essential. The School values diversity and is committed to equality of opportunity. The School of Chemistry holds a Silver Athena SWAN Award in recognition of our commitment
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learning and research in their chosen field and publish the results. The College’s academic environment provides favourable conditions for research, which will be undertaken freely and without oversight