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Responsibilities Quantitative method development and computational modeling (45%) -Develop, implement, evaluate, and advance computational approaches for estimating spatially and temporally resolved air-pollutant
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Mapping of Actors, Linkages, and Interdependencies (Field work) - Spatial Analysis and Scenario Modeling of Governance Innovations - Analyzing Vulnerabilities, Asymmetries, and Externalities
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position offers a unique opportunity to engage in innovative research projects in Singapore and Southeast Asia across a range of topics, including spatial epidemiology, infectious disease modelling, ecology
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transcriptomics, proteomics and spatial profiling, followed by functional validation in human iPSC-derived in vitro cell-based models. The successful candidate will investigate complement-mediated neuroimmune
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Full-Time Fixed-Term for 36 months This PhD aims to develop novel robotic monitoring and data processing methods to document changes in dynamic seafloor environments over large spatial scales
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models for bridging knowledge gaps, data scarcity and uncertainty gaps, and governance gaps related to monitoring the environment on which humans depend. A part of this is **spatial statistics of sensor
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, feed composition, and variables related to production-system typologies. Develop, adapt, and apply quantitative models to assess livestock interventions, including process-based, biophysical, spatial
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repair. Our research integrates single-cell and spatial multi-omics, human developmental tissue, stem cell and organoid models, perturbation approaches, and in vivo models to uncover mechanisms controlling
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laboratory in the Department of Neurosurgery at the University of Michigan Medical School. Using a combination of in vitro and in vivo modeling, analyses of clinical brain tumors samples and multi-omics
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of analyzing spatial and quantitative relationships in high content multiplex histopathology images Skills and experience of matched designs plus advanced statistical modelling of high-dimensional data, e.g