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of climate variability and change on child health outcomes across Sub-Saharan Africa by combining epidemiological data analysis with advanced Earth system modelling. The research will involve running
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biostatistics, infectious disease modelling, and geospatial analysis. You will be part of the Center for Statistics, a dynamic research team within the Data Science Institute, with extensive national and
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to work on selective spectral microscopic imaging (SSMI) for in-situ sensing applications. Many emerging applications, including microplastic detection, food safety, bioimaging, and materials analysis
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, that combines diffusion and transformer models, there are clear indications that the analysis of this data can be automated. This will open new avenues in data interpretation and building predictive models
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mini-applications that embody key AI workloads by combining multiple underlying kernels and the key data communications between them. You guide and help analysis and optimization of the performance
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(e.g. interviews, focus groups, content and discourse analysis) and quantitative data (e.g. surveys, travel behavior datasets); write academic publications and research reports; present research findings
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, representing the situation with Probabilistic Graphical Models such as Factor Graphs based on the fusion of multimodal sensorial information and integration at different layers of abstraction. The major
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
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everyday practices of street-level bureaucrats and private actors involved in eviction processes. Using a comparative mixed-methods approach, the project combines: Quantitative analysis of eviction court
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everyday practices of street-level bureaucrats and private actors involved in eviction processes. Using a comparative mixed-methods approach, the project combines: Quantitative analysis of eviction court