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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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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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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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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
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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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Zheng, and other collaborators to develop statistical and machine learning methods for medical decision-making in cancer prevention and early detection. Key areas of focus include, but are not limited
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of inclusivity and teamwork. - Engage in ongoing academic and intellectual life within CALS and Cornell University. Requirements • PhD in ecology, quantitative ecology, applied statistics, or a
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computational chemistry or physics will be preferred, but candidates with a solid background in statistics, computer science, and/or mathematics are also encouraged to apply. Programming skills (e.g., Python