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: Familiarity with (NGS related) software tools and packages such as bwa, STAR, bedtools, samtools, Picard, RSEM, GISTIC, GATK, Strelka, Seurat Prior experience in analyzing spatial transcriptomic data. Prior
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applicant must have professional proficiency in English (written and spoken). Desirable qualifications: Prior experience in working with economic models of migration, residential choice models, and/or spatial
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able to analyse complicated data. Good statistical knowledge and experience with geo-spatial analysis techniques is a benefit. Prior knowledge on wetland ecosystem functioning, and particularly on carbon
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education in the Department of Geography focuses on the following subfields: (a) Geographic information science: cartography, GIS, data analysis and visualization, spatial analysis and modeling; (b) Human
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Charles Henry Turner Post-doctoral Fellow, Department of Geography & GIS, College of Arts & Sciences
. Job Overview The Department of Geography and GIS at the University of Cincinnati, Ohio, seeks a fellow in geography, geospatial artificial intelligence (GeoAI), and spatial data science for its Charles
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, multi- layered spatial data sets (e.g. Remote Sensing and GIS), and contributing to the growth of the interdisciplinary Integrated Coastal Studies Program, which focuses on issues related
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in spatial analysis and data visualization Computer programming skills relevant for data manipulation and analysis Experience with creating and using complex data-driven analytical models using R
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platforms for integrating spatial and temporal information, harnessing remote sensing data, using climate information, understanding fuel accumulation and running physics-based or data-driven wildfire
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research. Interests and/or background in Arctic research, hydrological modeling, surface water fieldwork, community engagement, and/or spatial statistics are also a plus. PROJECTED START DATE There is
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computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models of reinforcement learning in the brain and