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of synchronised states using analytical and statistical techniques. Funding Notes This project is for self-funded or externally funded students only. References 1. Synchronisation of rotating turbulent (https://www
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. Applicants must: Hold a PhD (or equivalent) in Marine Science or a related quantitative discipline with a focus on elasmobranchs. Demonstrate experience in marine spatial and multivariate modelling
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with bioinformatics tools and software for data analysis (e.g. Seurat, SquidPy, Bioconductor). Strong understanding of statistical methods and data visualization techniques. Familiarity with spatial
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applications. Additionally, the grant holder will collaborate in the development of computational tools, including statistical software in R or Python and interactive web applications for spatial data analysis
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more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Development of statistical methods for estimating plant population size and change Mathematical
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society are required. Knowledge and skills of GIS and spatial studies are considered advantageous. To apply, please submit your application at https://careers.purdue.edu and include the following materials
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Bajcsy, PhD Information Technology Laboratory (ITL) National Institute of Standards and Technologies (NIST) Phone: 301-975-2958 Email: peter.bajcsy@nist.gov URL: https://www.nist.gov/people/peter-bajcsy
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Foundation (FAPESP), and combines statistical analysis, spatial methods, and qualitative research. Georeferenced data from the Military Police and the Municipal Secretariat of Urban Security will be used
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of GIS, spatial statistics, or other spatially relevant methods. Demonstrated experience applying machine learning and AI-based approaches to empirical disease, ecological, or biological datasets, with
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other