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Field
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for analysing movement and behavioural data. Strong knowledge of statistical analysis, experimental design, and reproducible computational research. Experience with scientific Python libraries (NumPy, SciPy
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods
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should hold a PhD (or be close to completion) in a relevant analytical and quantitative discipline, such as civil or transport engineering, transport modelling, mathematics, statistics, data science
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 11-Jul-26 Location: Irvine, California Type: Full-time Categories: Academic/Faculty Mathematics/Statistics Internal
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candidates able to conceptualize and statistically or mathematically link processes occurring at different spatial or temporal scales, or across levels of ecological organization (e.g., upscaling of microbial
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(15 ) Earth and Geosciences (17 ) Engineering (22 ) Environmental and Marine Sciences (14 ) Life Health and Medical Sciences (34 ) Mathematics and Statistics (8 ) Other Non-Science
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committed to having a supportive and productive relationship? For detailed information regarding application components, including requirements for the proposed project description, visit https
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will begin from June 2026. Education and Background PhD degree in a relevant quantitative discipline such as Bioinformatics, Statistics, Mathematics, Data Engineering, or Biomedical Engineering
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Research Associate, Department of Geosciences Posting Number req26900 Department Geosciences Department Website Link https://geo.arizona.edu/ Location Tucson Campus Address Tucson, AZ USA Position Highlights
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems Requirements: PhD in Mathematics, Computer Science