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Field
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multiparameter immunophenotyping, transcriptomics, proteomics, leukocyte functional assays, and statistical and computational biology to define mechanisms of cellular and humoral immunity to the transplanted organ
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happens in source areas is also essential for interpreting developments in nature reserves. You will be responsible for: statistical evaluation of air-quality monitoring network designs, including
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in the Biodiversity Dynamics and Conservation Group, a team of about 30 persons. Our group studies patterns of biodiversity and biodiversity change at various spatial and temporal scales, with a
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of statistical packages (Stata, R or equivalent). • Experience in spatial analysis and use of Geographic Information Systems (GIS). • Ability to work with large databases and data management tools. Languages
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hydro-climate studies. Strong background with GIS tools and spatial analysis techniques. Demonstrated expertise in climate variability assessment and the use of climate models. Experience with
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between biodiversity and climate change. The postdoctoral position is embedded in the the collaborative project Past to Future: towards fully paleo-informed future climate projections (P2F; https
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the services nature provides to people. The position will combine ecological data analysis with statistical and spatial modeling to quantify chemical impacts across multiple levels of biological
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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- statistical techniques used in spatial data analysis - scientific programming, e.g. Matlab, R, Python or Julia - designing and/or conducting field measurement campaigns in atmospheric
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evolutionary mechanisms: for example, heterozygote advantage (HA), negative-frequency dependent selection (NFDS) or spatially/temporally fluctuating selection (FS). Recently, new research showing that balancing