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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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knowledge of mathematics (e.g. linear algebra, probability, statistics, stochastic processes) Experience of developing in larger projects While we don’t expect applicants to know biology, applicants
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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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Max Planck Institute for the Study of Crime, Security and Law, Freiburg | Freiburg im Breisgau, Baden W rttemberg | Germany | about 5 hours ago
economics, sociology, or a similar discipline; a background in statistics; experience with experimental research; a strong interest in crime research and novel research methods; a highly collaborative
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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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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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) 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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-cell transcriptomics and modern statistical/AI methodology to address this gap using in-house developed cell atlases. We will develop and benchmark approaches that infer copy-number changes and CIN
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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
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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