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Field
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05.07.2026, Academic staff Our research combines mathematical modeling, numerical simulation, scientific computing, and data-driven methodologies to improve the predictive capabilities and
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, or uncertainty-modelling approaches for complex systems analyse infrastructure, spatial, temporal, networked, or urban systems data contribute to the preparation and submission of journal articles, conference
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, including spatial transcriptomics In vivo imaging of neural circuit deficits in zebrafish Pharmaco-behavioral profiling to identify pharmacological candidates Key responsibilities Analysis of molecular
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
new immune-epithelial-mesenchymal co-culture models; perturbation approaches to define region-specific transcriptional regulation of epithelial homeostasis; characterization of sputum and mucus
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theory, network science, resilience theory, disruption modelling, mobility systems, urban analytics, computational social science, agent-based modelling, causal inference, or spatial data science
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the spatial aspects of socio-technical systems. Data science skills and an interest in spatial modeling are highly desirable. Experience with multi-disciplinary teams deploying mixed methods in complementary
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Postdoctoral Research Associate – Geospatial and Systems Modelling This role will contribute to the delivery of the CIRCARB programme, a national-scale research initiative focused on defossilising
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of these interactions into soil and ecosystem models. Depending on the selected candidate, the research project can focus on statistical analysis of literature data, process-based modelling, or a combination of the two
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Post Doctoral Researcher Rinn Artificial Intelligence – Research & Innovation in Data Science and AI
and clinical characterization among the main objectives. One key aim of the group is to further the development of bespoke solutions for cancer imaging based on spatial analysis and kinetic modelling
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are governed not only by differential equations, but also by geometric constraints, conservation laws, symmetries, and interactions across multiple spatial and temporal scales. Developing mathematical