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considered, but priority will be given to those in the following areas. Artificial intelligence (with a focus on Machine Learning, Multi-agent Systems) Systems and networking Cyber security
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Computer Science, Engineering, or a related discipline, with demonstrated experience in Artificial Intelligence (AI) / Machine Learning (ML) research or application. Strong technical expertise in one or
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, such as Business, Computer Science, Data Science, Engineering, or a related field. They should demonstrate a strong combination of business acumen and technical expertise in AI and machine learning
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modelling, stochastic optimization, dynamic programming, and online learning algorithms; familiarity with sequential decision-making, multi-armed bandits, Thompson sampling, spatial matching, machine
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and machine learning concepts, such as data preprocessing, model evaluation, embeddings, classification, regression, or clustering. Ability to learn new tools, frameworks, and technologies quickly
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and machine learning concepts, such as data preprocessing, model evaluation, embeddings, classification, regression, or clustering. Ability to learn new tools, frameworks, and technologies quickly
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machine learning (ML), artificial intelligence (AI), operations research, data science, and industrial engineering, with applications to aviation, healthcare, sustainability, supply chains and
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; agent learning and adaptation; reinforcement learning and inverse reinforcement learning. o Machine Learning & Intelligence, including machine learning and adaptation; deep learning; computer
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; agent learning and adaptation; reinforcement learning and inverse reinforcement learning. o Machine Learning & Intelligence, including machine learning and adaptation; deep learning; computer
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support; agent learning and adaptation; reinforcement learning and inverse reinforcement learning. o Machine Learning & Intelligence, including machine learning and adaptation; deep learning; computer