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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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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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Artificial Intelligence and Machine Learning applications Computer Vision and sensor integration for agricultural applications Human-Robot Interaction in agricultural contexts Robotic Perception and
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agents, including uncertainty quantification at the agent’s level. The project will bring together ideas from Statistics, Probability, Statistical Machine Learning, Statistics and Game Theory and is an
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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
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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
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This research project aims to establish the theoretical and algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It
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qualification/experience in a related field of study. The successful applicant will have expertise in statistical modelling, epidemiology or machine learning and possess sufficient specialist knowledge in
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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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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