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tasks. Key Competencies Integrates GIS, remote sensing, and environmental data for spatial modelling. Proficient in or able to learn ecosystem service software (e.g., InVEST, ARIES). Strong analytical
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and spatial conditions influence energy performance and thermal comfort. By combining spatial mapping, data modelling, and fuel poverty metrics, the project will identify where health risks are most
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, developing spatial statistical models, and translating results into actionable insights for policy and adaptation. The strength of the project lies in its interdisciplinarity, combining atmospheric science
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A crystal in space represents a distinct state of matter, with spatial periodicity in its lattice structure underpinning its band structure and optical properties. This project concerns time
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information, for example data derived from remote sensing, use point process models from the field of spatial statistics to model clustered patterns across the landscape, and develop methods for estimating
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data. This position offers an exciting opportunity to work at the intersection of cancer biology, spatial multi-omics, and artificial intelligence. More information: https://digitalhealth.tu-dresden.de
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Statistics we conduct research within the theory and implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational methods
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data efficiency. Decision Making/Autonomy (10%) – Lead architectural and data design decisions; prioritize experiments aligned with program milestones; evaluate trade-offs between model accuracy and
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and Statistics we conduct research within the theory and implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational methods
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implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation