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staff. We conduct research in several areas: analysis of high-dimensional data, Bayesian methods, spatial-temporal models, non-Gaussian modeling, applied research in social science, as well as stochastic
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in Data Science and Statistics with expertise in the application of data science to spatial and space-time data from problems throughout the geosciences. The Department of Applied Mathematics and
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to the Institute’s needs. Requirements for candidates: Proven experience in advanced hydrological modeling (e.g., conceptual or physically based spatially distributed models), particularly with SWAT+, SWAT-MODFLOW and
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crane. The successful candidate will build reproducible machine learning pipelines, integrate detections into spatial ecological models, and generate conservation-relevant outputs for regional partners
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tissue using genetic mouse models, functional screens, and single cell and spatial omics technologies. More details about the laboratory: https://www.ibt.cas.cz/en/research-laboratories/laboratory
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. The PhD (M/F), to be recruited in the context of the ERC StG MULTI-viewCELL, will be working on the development of a new method combining machine learning and biophysical modelling to model embryo
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, or agricultural greenhouse gas estimation. Proficiency in working with spatial data and geospatial tools. Interest in science–policy interfaces. What you will do Develop and apply biophysical and economic models
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Lab aims to reveal how metabolism, oxidative stress, and cell death converge to shape cell fate. For more information about the Henry Lab, please visit: https://thehenrylab.squarespace.com/ For more
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analysis of spatial-omics and imaging data, developing a framework for simulations, simulating epidemics on social networks, building generative models to improve computation time for simulations, and other
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. The main activities include: (i) the experimental implementation and characterisation (spectral, spatial and intensity noise) of frequency conversion devices using chalcogenide components/materials (crystals