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, BioM will unite ecology, statistics, and philosophy to improve the modelling and governance of biodiversity under uncertainty. The project develops process-explicit, hierarchical models that capture key
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biology, microbiology, environmental science and environmental engineering as well as disease ecology. The Linnaeus University centre in Ecology and Evolution in Microbial Model Systems (EEMiS) in Kalmar
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related to models and multiple sources of data describing ecological dynamics. The PhD project will address the following aims: 1) Develop efficient tools for learning about models from data, 2
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challenges. The ASE integrates earth and environmental life science, ecology, engineering and technology, human ecology, humanities, and the social sciences to address key issues of the environment and
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Ecology and Evolutionary Biology, Environmental Science, Genetics and Genomics, and Bioinformatics and Computational Biology. Department Unit/Website: https://www.eeob.iastate.edu/ Proposed Start Date
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at the rank of Assistant Professor in Forest Ecology and Modeling Research. This 100% research appointment will be administratively based at the Blackland Research and Extension Center in Temple, Texas, with
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under my supervision to support research related to AI-driven modeling of forestry systems, plant physiological processes, and ecological traits. The position will focus on developing computational models
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mathematical ecosystem modelling with experimental data. Our lab strongly supports cross-disciplinary approaches to research. We straddle the clusters of Molecular Microbiology and Ecology and Evolution, and you
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the application. Required qualifications: Solid insights in marine ecology Programming skills in Fortran, Python and R Demonstrated skills in statistical analyses and modelling Capacity to work with complex data
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statistical and/or causal inference skills; ● Strong background in ecological theory and modeling. ● Experience leading peer-reviewed publications and/or reports; ● Excellent communication and collaboration