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Field
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Atlantic locations. Coordination, logistics, and management of associated sampling campaigns. Processing of algae for blue carbon determination. Statistical analysis of results using the R software package
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as evidence of ongoing CIN. This PhD will work at the leading edge of single-cell transcriptomics and modern statistical/AI methodology to address this gap using in-house developed cell atlases. We
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to the development of non-destructive methods to monitor natural degradation, using advanced analytical and statistical approaches. • Develop, implement, and refine models that integrate micro-environmental
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molecular ecology, population genetics, and statistical analyses is required. Interest and prior practical experience with molecular ecology of zooplankton is preferred. Practical experience with Calanus and
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) economics, psychology or a related discipline you possess quantitative statistical and/or econometric skills you have excellent writing and verbal communication skills in English you are interested in doing
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well as in urban areas. See also: https://www.slu.se/en/about-slu/organisation/departments/ecology/ About the position The researcher will work in the field (in southern Sweden), with statistical analyses, and
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laboratory work (DNA extraction, PCR, sequencing workflows) Bioinformatics and statistical analysis (e.g., R or Python) Biodiversity assessment or ecological community analysis Fieldwork experience in
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eNSEMPLE. It is an interdisciplinary project at the interface between Statistical Physics, Data Science, Network Science, Computer Science and Sociology, and will involve collaborations with researchers from
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grades. Excellent language skills in English. Ability to speak and understand German and/or French is an advantage. Excellent knowledge of research methods and statistics; ideally you are familiar with
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particular emphasis on trait dimensions related to tolerance, movement, and interaction. By integrating multi-taxa field data, trait-based ecology, experiments, and advanced statistical analyses, TRACE aims