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Field
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: Conceptualisation and synthesis of data integration and visualisation workflows. Data management and the development of knowledge graphs Development and application of AI and machine learning methods and pipelines
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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compliance (5%). •Conduct research on artificial intelligence (AI) and machine learning (ML) to analyze large-scale biological, genomic, metabolomic, and phenotypic dataset (25%). •Investigate the genetic
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energised — not deterred — by problems that sit between physics, learning and the messy real world. Your experience and profile: a PhD (completed or near completion) in Machine Learning, Computer Vision
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well as machine learning and multivariate decoding of neuroimaging data to predict subjective experiences and individual differences. Successful candidates will be supported in building a research program at the
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..) based on candidate expertise and interest. -Collection of data and keeping of detailed records of results, as well as utilizing computer programs and databases to conduct analyses. -Evaluate data, drafts
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) Computer, Information, and Data Sciences (17 ) Earth and Geosciences (21 ) Engineering (29 ) Environmental and Marine Sciences (14 ) Life Health and Medical Sciences (51 ) Mathematics and
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, and machine learning, the program prepares graduates to drive progress in fields like renewable energy, 5G, cyber-physical systems, and smart infrastructure. University Information The University
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The successful candidate will have completed a PhD in chemistry education or related field (ABD will be considered), and will be performing research in line with the PI's research program. The postdoctoral scholar
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utilize computational systems and applicable software, including breeding databases, perform statistical analysis, present data, and perform other computer-related tasks. Excellent written and oral