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Field
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, the project aims at developing a method that can derive ground-level concentrations of air pollutants on a high spatial resolution directly from satellite retrievals. Secondly, the outcome of
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will focus specifically on investigating hillslope-riparian zone-stream connectivity at the reach-to-catchment scale for a better understanding and spatially distributed prediction of subsurface
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learning and memory on different spatial and temporal scales requires multimodal imaging techniques at various levels and generates huge amounts of high-dimensional data, reaching levels of complexity
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project partners · Very good language skills in English and German Tasks · Independent work on a research project, including method development for spatially resolved strain characterization
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Systems Engineering (ICE-1), our focus is on developing models and algorithms for simulating and optimizing decentralized, integrated energy systems. These systems are characterized by the high spatial and
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European Molecular Biology Laboratory (EMBL) | Brandenburg an der Havel, Brandenburg | Germany | about 2 months ago
-cell and spatial omics, precision medicine (Genome Biology ), multi-scale models in space and time for organelles and cells (Cell Biology and Biophysics ) or collectives of unicellular and
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Leibniz Institute of Ecological Urban and Regional Development (IOER) • | Dresden, Sachsen | Germany | about 2 hours ago
Programme duration 6 semesters Beginning Other Application periods DLGS accepts competitive applications for: Current call (deadline: 1 September 2026) https://dlgs-dresden.de/application/funding/scholarships
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to develop sampling strategies that go beyond similarity in the embedding space by integrating domain knowledge such as spatial distance, sensor metadata, or existing maps. A second part of the project
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spatial omics data and to uncover the regulatory mechanisms driving cellular differentiation during vertebrate embryonic development. In this project, you will develop quantitative machine learning models
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doctoral education in the interdisciplinary field of geoinformatics. GI (geoinformation) is a powerful economic factor: around 80% of all decisions in society are said to have a spatial component, due to