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tissue formation, and limited spatial precision. Building on our recent advances in enzyme-triggered electrode fabrication in living systems (Strakosas et al., Science, 2023, https://doi.org/10.1126
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. 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 heterogeneity and
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Arabidopsis thaliana or a comparable model plant system. Very good written and oral English language skills. Meriting qualifications The following qualifications are not required at the point of appointment
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or heterogeneous environmental datasets Familiarity with spatial analysis, GIS, or geospatial data workflows. Experience with machine learning, modelling, or systems analysis approaches Interest in resilience
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: Participating in the planning and execution of preclinical studies of targeted radiopharmaceuticals. Working with experimental tumor models, including cell culture, establishment of tumor models, and monitoring
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Developing analytical methods to integrate different types of sequencing-based DNA data. Developing computational models for prognosis and treatment prediction Integrating various types of spatial single-cell
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to apply Website https://uu.varbi.com/en/what:job/jobID:970239/type:job/where:39/apply:1 Requirements Additional Information Work Location(s) Number of offers available1Company/InstituteUppsala
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applications in different project contexts. This may include data analysis, modelling, literature reviews, and interaction with relevant stakeholders. The results are expected to contribute increased knowledge
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application! This recruitment is linked to the Impact Innovation program Swedish Metals and Minerals – an initiative of Energimyndigheten, Formas and Vinnova. Read more: https://impactinnovation.se/program
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Development Design new statistical and machine learning models tailored to this emerging omics modality. Multimodal Data Analysis Work with high-dimensional datasets combining quantitative RNA features