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.2022111885 https://doi.org/10.1016/j.tplants.2023.04.006 . To reach its aims, the lab uses a large set of interdisciplinary approaches, including genetics, molecular methods, and genomics. About the project
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, including how your background, interests, and career goals align with its objective PhD diploma or a letter/information indicating the expected defense date Transcript of all modules and results from
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remote sensing data. What you will do Changing fire dynamics will be studied using a Dynamic Global Vegetation Model (DGVM), allowing us to quantify different mechanistic processes. Using high-resolution
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hydrogen more affordable by developing advanced models while working with partners across Europe? Information This position is part of a large European collaborative project aimed at accelerating renewable
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(programming and advanced data analysis, experience with the analysis of large and complex datasets, GIS, data management) Process-oriented thinking and hydrological process understanding Some experience in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
Benefits and Services click here Quick Link https://unc.peopleadmin.com/postings/322997 Posting Contact Information Department Contact Name and Title Stephanie Fleming, HR Consultant Department Contact
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national center for biodiversity information. Among other things, Naturalis runs large-scale ML services for nature recognition, including bioacoustics algorithms developed in the team. What you will do
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for data management and analysis (e.g., STATA, SPSS, SAS, R), and familiarity with AI tools for data processing, nutrient coding, and analysis of large food and dietary datasets, and the ability to work well
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» Surface physicsYears of Research Experience1 - 4 Additional Information Eligibility criteria Applicants should hold a PhD in experimental condensed matter physics, quantum electronics, nanoscience, quantum
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health