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at the rank of Research Assistant Professor in applied probability, data science, machine learning, and spatial statistics. Candidates with a strong background in the development of novel models and original
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consequences for essential ecosystem processes. In the framework of the Biodiversity Exploratories (https://www.biodiversity-exploratories.de/en/ ), funded by the German Research Foundation (DFG), the project
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hours; Health insurance, employee benefits, and life in a pleasant and safe city; Competitive salary. Where to apply E-mail vladimir.remes@upol.cz Website https://pracuj.upol.cz/nc/zprava/clanek/postdoc
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University of California Agriculture and Natural Resources | Oakland, California | United States | 2 months ago
with team members. Responsible for statistical integrity, adequacy and accuracy of data, and the timeliness and effectiveness of all data collection and reporting systems. 10% Study design and proposal
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person with an interdisciplinary background and training. QUALIFICATIONS: REQUIRED: o Very strong statistical and analytical skills with a strong background in causal inference approaches (e.g
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the following: Generates, compiles and presents statistical data with appropriate conclusions, recommendations, etc. pertinent to research activity. Reviews and analyzes scientific data, scientific reports
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multidisciplinary experience in combining integrative computational immunology – data-driven, state-of-the-art single cell resolution and spatial methods, machine learning and kinetic modeling – with integrative
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for the other courses may include introductory computational methods, statistical methods, text analysis, network analysis, spatial analysis, societal impact of AI, digital media, art and technology, social media
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. Where to apply Website https://brgm-recrute.talent-soft.com/job/job-post-doc-raw-materials-lca-for-the… Requirements Research FieldGeosciences » OtherEducation LevelPhD or equivalent Skills/Qualifications
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of observed meteorological elements at all spatial scales. ICV also constitutes an important source of uncertainty in climate model outputs, especially regarding the occurrence of climatic extremes. Furthermore