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The project will require coding for data analysis and statistics, as well as NGS data analysis. Experience with either of these would be advantageous but an eagerness and commitment to learn is more important
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request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting diversity and ensuring equal opportunities in our workforce. This information will be
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algorithmic perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems
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cognitive neuroscience. You have documented experience in experimental research on learning or decision-making with knowledge of computational models (e.g., reinforcement learning). Good statistical skills
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research programme at Oxford. Candidates should hold a PhD in biomedical engineering, computer science, medical physics, statistics, or a related field. A strong track record of first-/senior or co-author
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they would design, organize, and conduct advanced quantitative (statistical, spatial, etc.) analyses relevant to climate equity, environmental justice, and/or environmental health; translate complex data and
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design, statistical sampling and analysis of large, multi-taxa biodiversity datasets. Expertise in landscape-level biodiversity and production analyses using R, QGIS, Google Earth Engine. Extensive
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information, contact Dr. Jun Wang at jun-wang-1@uiowa.edu . Education Requirement: Ph.D. (or equivalent) in Atmospheric Sciences, Chemical Engineering, Environmental Engineering, Applied Mathematics/Statistics
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research into planet formation/protoplanetary discs or the ISM/star formation and may also have some experience in statistical methods and/or machine learning. Dr Winter and QMUL are committed to improving
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of mole activity and soil health and biodiversity, collecting data on visitor perceptions of moles and their management, and analysing findings using statistical modelling approaches. The role provides