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background in analyzing large astronomical datasets is essential, particularly in characterizing non-isotropic distributions and spatial-kinematic properties using Gaia and/or DESI data. Proficiency in
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, evolution, ecology, biology, psychology, economics, computer science) or engineering completed by start date Demonstrated academic excellence and research experience, especially published peer-reviewed papers
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if the candidate is expected to have a keen interest in digital history, other team members will do the advanced computational analyses in collaboration with the rest of the team’s domain experts
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] Subject Areas: Engineering / Materials Science , Mechanical Engineering Appl Deadline: 2025/07/11 11:59PM (posted 2025/06/12, listed until 2025/12/12) Position Description: Apply Position Description
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for adaptation to sea level rise along the Maine coast. This 18-month grant-funded position will be supported in partnership with Maine Coastal Program (MCP), Maine Geological Survey (MGS), and faculty from
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contributing to specifically the area of handling spatial data to assess the distribution of several soil properties and fungal communities using samples collected from multiple habitats and land use types at a
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distribute information for meetings, conferences and publications and conduct occasional meetings with project sponsor personnel; Other duties as assigned Adaptability, excellence, and passion are vital
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39 Faculty of Computer Science Startdate: 01.07.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 30.06.2029 Reference no.: 4027 Among the many
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soil microbial communities. You will be contributing to specifically the area of handling microbial data to assess the spatial distribution of several soil properties and fungal communities using samples
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program, focusing on intermediate wheatgrass, perennial rye, and perennial wheat. The candidate will design and implement appropriate breeding strategies, integrating modern genomic approaches where