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competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics. This PhD project falls under Research Thrust RT4 on Reliability and Trustworthiness
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to date focus on just one layer, understanding what keeps AF going is challenging. This PhD project aims to bridge that gap by combining advanced machine learning tools with a new experimental protocol
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scan data is desired Familiarity with analytical tools such as R or Python for statistical and phylogenetic comparative analyses Experience with scientific writing and publishing in peer-reviewed
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Your Job: You will develop instrumental analytical and theoretical methods to determine the origin of hydrogen and, in particular hydrogen carriers (including methanol, LOHC systems, formic acid) by
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project, co-funded by the Innovation Fund Denmark and the Department of Management, Aarhus BSS, Aarhus University. Candidate profile We are seeking applicants with strong knowledge of data analytics and
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Are you passionate about artificial intelligence, data analytics, and cutting-edge engineering applications? Join our interdisciplinary research team and contribute to the future of Non-Destructive
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interpretation of the data generated and that’s where this project comes in. You’ll be applying metagenomic techniques to respiratory samples and developing analysis and interpretation approaches that facilitate
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offering PhD positions for students with a background in data science, computer science, computational science, or a domain science with a strong focus on computational science, and an interest in training
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| £20780 + £2500 industry top up (per annum (tax free)) Overview This exciting, fully-funded PhD opportunity invites applications from candidates with a robust foundation in data science, modelling, and