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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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Transformation (GALLANT): https://www.gla.ac.uk/research/az/sustainablesolutions/ourprojects/gallant/ . This post will be based in Work Package 2 ‘Biodiversity and societal benefits of ‘natural’ urban habitats
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, and spatial organization, crucial especially in early developmental stages but relevant throughout life. Drawing from cellular and molecular biology, it delves into embryology, morphology, genetics
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preprocessing; Integration of geospatial and soil data into databases. Data processing and analysis: Application of geoprocessing and spatial analysis techniques; Development and calibration of predictive models
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the influence of the engine plume on the release of emissions into different atmospheric layers. Numerical model to describe the temporal and spatial dispersion behaviour of engine exhaust gases in the atmosphere
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-range of research activities which encompass laboratory, field and modelling studies related to atmospheric chemistry, air quality and climate. This research project is called Partnership for Evidence and
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. This simulation environment will exploit the unique features of currently available AI models and include two layers: the spatial mapping one (placing the chargers where the people need them to be), and the power
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for the Anthropocene. Global Ecol Biogeogr 27, 760–786. https://doi.org/10.1111/geb.12729 Hughes, S., Kunin, W., Ziv, G., & Watts, K. (2023). Spatial targeting of woodland creation can reduce the colonisation credit
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Help push the boundaries of urban wind modelling by developing efficient
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stem-like cell (GSC) models by sampling multiple distinct tumour regions to recapitulate their post-surgical and pre-therapy features, as well as their intra-tumoural heterogeneity (https://bit.ly