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PhD: Semantic Modelling of Geodata Sources and Geo-analytical Workflows Faculty: Faculty of Geosciences Department: Department of Human Geography and Spatial Planning Hours per week: 36 to 40
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passionate about statistical methodology and motivated by biomedical applications? Join our team on development of latent variable models for multi‑omics and longitudinal data and help advance data‑driven
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on correlation-based machine learning. When an agricultural system fails due to compounding climate extremes - like a simultaneous heatwave, drought, and ozone pollution spike - standard models can forecast the
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hidden patterns from them? Do you enjoy exploring mathematical models and working with network data? Join our team! Job description Complex systems are often modeled with networks, structures where
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and spatial modelling. This research is part of two Horizon Europe projects: WildCard and NatuRISE. The work will be carried out at the Institute for Environmental Studies (IVM) in collaboration with
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land-use and socio-economic simulation models to inform land use planning and policy still inadequately capture many of the benefits of nature restoration, especially those that emerge through spatial
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May 2026 Apply now Are algorithms neutral tools, or do they actively shape the world they model? In this PhD, you will bridge the gap between building and critically studying Human-Centred AI systems
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: formulate and analyze stochastic models of evolving populations using methods from statistical physics, applied probability, and population genetics; develop inference frameworks that link model predictions
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learning algorithms. Personalizing user interactions by building models that adapt explanations to specific knowledge levels and interests of users, so that user modelling and formal reasoning transform
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—to macroscopic, population-level observables in rapidly evolving pathogens such as SARS-CoV-2 and influenza. Concretely, you will: formulate and analyze stochastic models of evolving populations using methods from