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focus on linguistics and cognitive science. It unites ca. 20 research projects from different German universities, plus international collaborators, from diverse academic disciplines. The position is part
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in different learning and educational contexts (e.g., in the family, in different educational institutions, and in the context of lifelong learning). Your tasks Research and publication activities with
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biodiversity patterns, utilizing both spatial and statistical expertise. At this stage of the subproject of the CRC the project aims to evaluate whether ecological patterns previously identified in the RESIST
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animals. Our strategy will allow us to compare stress responses and behavioural data between different species and classes of pathogens, leading to important synergies by using standardised methods
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programming language such as C or Fortran Strong expertise in data analyses and statistics Experience in ecological or environmental modelling Documented ability to publish scientific papers in international
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different fishing scenarios, including: Effects of environmental change, e.g. in temperature Shifting abundance and distribution of major krill predators (e.g., whales, penguins, seals) Changing fishing
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datasets Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl, C++, R) Well-developed collaborative skills We offer The successful candidates will
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, imaging). • Solid foundations in signal processing and statistics. • Experience with machine learning for regression (e.g., tree-based methods, neural networks) • Hands-on experimental skills: ability and
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | 3 months ago
well as advanced statistics and novel microscope methods to design your project and analyse your data Experience in animal work as well as neuroscience methods like primary cell culture, in vivo surgeries
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on disaster risk management and climate adaptation, using probilistic risk modelling, applied statistical methods to evaluate risk management and adaptation measures in the agricultural sector, mainly in low