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microbial species distributions respond to ongoing climate change. The four-year project will build on time series data on microbial biodiversity changes across large temporal and geographical extents, based
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 28 days ago
operates the first Czech quantum computer named VLQ. For more details, see www.it4i.eu . Activity description: · conduct research in machine learning with emphasis on computer vision, · develop and evaluate
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 30 days ago
operates the first Czech quantum computer named VLQ. For more details, see www.it4i.eu . Activity description: · conduct research in machine learning with emphasis on computer vision, · develop and evaluate
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to identify global patterns of fungal species distribution. Within the project, the person will be involved in the study of the structure of soil fungal communities using our in-house global databases of fungal
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preparation and testing or powder mixtures, and then to devise predictive models (possible using machine learning approaches) for the estimation of mixture properties from pure component propeties. The PhD
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to climate change and variability Hydrological processes in organosols and peat-affected soils Modeling Hydrological Extremes Using Machine Learning Spatial and time distribution of precipitation within
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distribution of plant-associated fungi and their symbioses? How plants protect reproduction from heat stress; from models to crops Identification and Functional Characterization of Resistance Genes Conferring
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Taxonomy, phylogenetics, distribution, morphology of animals with special focus
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research and applications of advanced spatial data analysis methods, data collection, and interpretation of remote sensing data, database system theory, mapping, spatial data distribution, development of new
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: Mathematical modeling and statistical data analysis. Evaluating data as potential predictors explaining the spatial distribution of archaeological or epigraphic finds (e.g., analysis of variance, correlation