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prototyping with access to Lancaster's high-performance computing facilities. Essential Requirements • PhD in Machine Learning, Computer Science, Computational Neuroscience, or related field
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experience of machine learning, multiwavelength imaging and data analysis are encouraged to apply. Prospective candidates are encouraged to contact Dr John Stott (j.p.stott@lancaster.ac.uk ) for further
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bringing together observations and global atmospheric models using innovative statistical and machine-learning approaches. It will provide the first clear attribution of how different physical, chemical and
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will be spent on both aspects of the role. You should have a postgraduate degree in Statistics, machine learning or a related discipline and a track record of methodological research relevant to Prob_AI
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mathematical machine learning and AI methods, or applied mathematics, to solve challenging problems. Your research will have potential for real-world application in areas including, but not limited to, cyber
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classification algorithms including machine learning); and the output data and interpretability. The project “SORS in the community” is funded by the EPSRC (https://www.ukri.org/news/new-tools-aim-to-improve-early
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a PhD in mathematics or a related discipline and be able to demonstrate previous research experience in using mathematical machine learning and AI methods, or applied mathematics, to solve challenging
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People from Deepfakes Project. We are looking for a software/machine learning engineer (or similar) to work in an interdisciplinary team reporting to Dr Sophie Nightingale (Principal Investigator
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bringing together observations and global atmospheric models using innovative statistical and machine-learning approaches. It will provide the first clear attribution of how different physical, chemical and
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to work alone and as part of a team. Excellent computer skills including Microsoft Office and the ability to learn new software packages and systems. A curiosity and willingness to learn both for your own