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-country survey datasets for comparative analysis. Conceptualize and refine a theoretical framework integrating intersectionality and stigma processes. Develop and code a Bayesian meta-regression to pool and
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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 20 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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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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study examining common elements in decisions across different contexts (risk, uncertainty, time; gains, losses, and mixed domain choices). Applying Bayesian techniques to develop stochastic models
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single cells make decisions during differentiation, in particular during development. Building on Bonsai, a Bayesian framework that leverages tree structures for distortion-free exploratory analysis
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. quantitative and/or qualitative counterfactual-based approaches, Difference in Difference models, Qualitative Comparative Analysis, Bayesian hierarchical modelling); o Experience working with and synthesizing
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. The PDRA will quantify the differences in calculated and measured experimental conditions by adapting the Geodetic Bayesian Inversion Software ( https://doi.org/10.1029/2018GC007585) ). Working alongside our
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different applications are being developed in the project. The experimental programme involves development of high-throughput experimental capability (at Imperial College London). The SRE group (Prof Lapkin
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), and physiological parameters in the study of animal behaviour; a strong background in data analysis using R, preferably experience with Bayesian statistics and social network analysis; lab experience
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, demographic modelling, Bayesian hierarchical models and/or modelling with multiple data streams • Experience with data science and biodiversity informatics, in particular handling of scientific collection