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Field
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Machine learning/AI based classifiers Proficiency in coding using R and Python and other similar languages High level analytical capability Ability to communicate complex information clearly Informal
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and experience in developing and implementing machine learning/AI solutions using relevant languages and frameworks Informal enquiries can be made to Dr Hazel Wilkinson, Deputy Director IDAI, email
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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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population genetics, bioinformatics, computational biology, statistics or probabilistic machine learning and computer science. Experience of working with large genotyping or sequencing data sets A proven
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the ability to develop novel theory. They must also have strong development skills, to enable them to lead the process of prototyping new interactive systems with sensors, build machine learning
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
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, data sciences, or a related subject, ideally with a focus on utilising large-scale health/biomedical data and the application of advanced data analysis methods such as machine-learning. Equivalent
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machine learning/AI or cybersecurity, or both, as evidenced by a strong track record of publications in leading journals and conferences in relevant areas. Software programming skills. To be successful
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, data sciences, or a related subject, ideally with a focus on utilising large-scale health/biomedical data and the application of advanced data analysis methods such as machine-learning. Equivalent
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postgraduate-level research in Computer Science, Cybersecurity, Information Security, Information Technology, Artificial Intelligence, Machine Learning, or a related field, have experience with securing AI