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International travel may be required for this role. Background This post will advance the application of Machine Learning (ML) in weather forecasting and hydrological prediction. The Research Fellow will develop
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foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing can be
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large scale flow network simulations, machine learning, and methods from topological data analysis, to a broad set of problems. Examples include modeling vertebrate and invertebrate circulatory systems
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datasets, performing statistical analyses and machine learning approaches to identify biomarkers of treatment responses. The candidate will also develop and implement bioinformatics pipelines in a high
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical technology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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managing and curating large datasets and with machine learning techniques preferred. Excellent oral and written communication skills and the ability to perform both self-directed and guided research
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within the role to pursue an independent research project in the general remit of gene expression and the lab. Candidates with interest or experience in machine learning, artificial intelligence and
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image analysis Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software and algorithm development, modeling machine
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, and expertise in computational methods, data analysis, software and algorithm development, modeling machine learning, and scientific simulation Ability to work well in an interdisciplinary environment
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Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software and algorithm development, modeling machine learning, and scientific