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medical applications. Federated Bayesian learning offers a solution to those problems by allowing multiple participants to train machine learning models collaboratively, without sharing any data. Bayesian
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are of interest. The primary objective of this PhD project is to develop adaptive statistical models for marked spatial and spatio-temporal point processes. Many real-world systems exhibit substantial spatial
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for hypergraphs and partially ordered sets (POSets), funded by the Swedish Research Council. This project is concerned with saturation problems for two classes of combinatorial objects: hypergraphs and posets
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science with a focus on bioinformatics. We offer an international, stimulating, and collaborative research environment where your scientific career development is promoted. The project aims to track strain
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). This project will employ cell models with a thick glycocalyx as well as molecularly defined molecularmodels of the glycocalyx. You will establish a pipeline for single-particle tracking of viruses in three
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and visualization in a Microbial Cell Atlas. This position aims to develop key software components to enable this mission. The results of this project will be used to track new pathogens, combat
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period marked by shifting EU politics, geopolitical uncertainty and climate change. The project investigates how forest governance is shaped by tensions between environmental objectives, economic interests
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at the Faculty of Medicine are enrolled in the faculty-wide doctoral training programme. The programme comprises 25 credits and is offered in two study tracks: 25 credits across 8 semesters (4 years) or across 12