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approaches. The PhD will develop and apply optimization-based energy system models to analyse whether spatially coherent urban and energy configurations can be operated efficiently under realistic physical
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the molecular signatures of proteostasis loss and identify early markers of proteostatic failure. The role combines wet-lab spatial biology with computational approaches. You will work across models and scales
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particular, the research project will focus on inferring trajectories from spatial transcriptomics data modelling at the same time the cells evolution in gene expression and in space. Required skills : We
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. The main objectives of this PhD thesis are thus: - To evolve existing dual source energy balance retrieval model to incorporate physiological controls on GPP through stomatal regulation - To test and
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focus on the conceptualisation and prototyping of spatial data infrastructures and registries for space environments and objects. The role involves research into spatial data models for representing
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and/or spatial genomics datasets is a plus but not necessary. Proficiency in programming (e.g., Python, R) and familiarity with common bioinformatics tools and packages. A PhD in developmental biology
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. In particular, the research project will focus on inferring trajectories from spatial transcriptomics data modelling at the same time the cells evolution in gene expression and in space. Required
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. Applicants must: Hold a PhD (or equivalent) in Marine Science or a related quantitative discipline with a focus on elasmobranchs. Demonstrate experience in marine spatial and multivariate modelling
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. Spectral dynamics of the conditional Lyapunov vector (https://www-cambridge-org.sheffield.idm.oclc.org/core/journals/journal-of-fluid-mechanics/article/spectral-dynamics-and-spatial-structures
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and application of deep learning models from drones and satellite remote sensing data to identify urban risk areas for mosquito-borne diseases in East African cities. This position is part of an inter