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. This research project has a dual focus. On the one hand, you will be involved in analysis of spatial, single-cell and multi-omics data to efficiently characterize the different molecular layers. This will be done
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mimicked with in vivo models of metastasis, which provides unique opportunities to mechanistically dissect what drives the different cell states. You will link clinically relevant phenotypes to putative
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, with a focus on biodiversity conservation. You’ll contribute to high-impact publications and collaborate across disciplines to deliver research that makes a real-world difference. In addition a
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. The observational data for each of these instrumental techniques is affected by structures that can be only accurately analyzed at the different scales by the other instruments. Our general science goal is to study
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this aim and to collectively, & individually, make a real difference. The role A research fellow position is available to work on the project “Dynamic and Adaptable Monitoring of Greenhouse Gas Emissions
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development), and strong programming skills (Python preferred). As a people-orientated individual, you will have the ability to influence and engage collaboratively with AEGIS, UoN and other stakeholders. As a
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. change detection, semantic segmentation, or multimodal fusion, experience in deep learning for image analysis using time series satellite data, excellent programming skills (Python, PyTorch/TensorFlow
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and vice versa. Food system models represent the different activities within food systems (such as production, processing, distribution, and consumption) and incorporate multiple drivers and feedback
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to the single-cell level to answer a fundamental question: Why do metabolic diseases, especially mitochondrial defects, affect different cell types in different ways? Your mission As a research assistant, you
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cortex of mice. We will focus on neuronal micro- and macro-circuits that influence our feeding behavior, which includes the prefrontal cortex with a focus on selection between stimuli of different value