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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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/Machine Learning engineers. Want to leverage your skills to usher in the era of personalized disease modeling? The Digital Twin Innovation Hub is currently seeking skilled and experienced individuals
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-diffusive(-thermal-chemical) behavior of fiber-reinforced composites at the micro/meso-scale. These models will incorporate uncertainty via stochastic inputs, such as random field representations of spatially
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the spatial distribution of woodburning emissions. Integrate observations into inversion modelling to refine regional and national emission inventories. Model the impact of woodburning on UK air quality and
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, Statistics, Bioinformatics, Applied Math, or related field. MS or PhD degree is preferred but not required. Required qualifications ? Substantial expertise in training deep learning models and tuning large
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spatial transcriptomics, with the ultimate goal to understand and harness immune responses in human diseases. The Engblom and Villablanca labs form a tight-knit collaborative team of scientists with diverse
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accessibility modelling, typological mapping, and studies of everyday mobility practices, with a particular focus on vulnerable groups and their access to urban services. The PhD project will explore how built
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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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will involve (but not be limited to) applying sophisticated mouse genetic models of cancer and conditional gene targeting, single-cell RNA-seq, spectral flow cytometry, multiplex imaging and spatial
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investigate how intra-tumour heterogeneity (ITH) shapes the immune microenvironment in primary and metastatic breast cancer. Using spatial transcriptomics and mouse models, the candidate will map immune niches