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using mouse models for neurodevelopmental disorders and brain inflammation. Run spatial omics approach including multiplexed protein imaging and transcriptomics. Collect and analyze data from genome-wide
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will work with data collected from the field to the spatial scale, and investigate spatial optimization approaches to improve the model parameterization at the spatial scale. We expect that you will be
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will work with data collected from the field to the spatial scale, and investigate spatial optimization approaches to improve the model parameterization at the spatial scale. We expect that you will be
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disease, with a strong focus on fibrosis and inflammation. Over the years, we have developed an advanced translational toolkit, including human precision-cut tissue slices, a unique organotypic model
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mechanisms of cell signalling in several cellular models. The team combines omics technologies with bioinformatics, and functional validation of candidates by biochemical, cell biology, and imaging methods
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on regulatory mechanisms of cell signalling in several cellular models. The team combines omics technologies with bioinformatics, and functional validation of candidates by biochemical, cell biology, and imaging
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] that process information in temporal rather than spatial modes to reduce their footprint. The project involves a collaboration between DTU Electro (Senior Researcher Mikkel Heuck) and Harvard University (Dr
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contributing to specifically the area of handling spatial data to assess the distribution of several soil properties and fungal communities using samples collected from multiple habitats and land use types at a
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model with a farm model Run scenario analysis to identify management practices with the largest mitigation potential, both spatially and temporally Coordinate and contribute to dissemination
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advanced contextual spatial and temporal modelling approaches. You will work on combining multi-source data such as field observations, laboratory measurements, environmental data, and drone- and satellite