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Uppsala University, Department of Information Technology Are you interested in probability theory, statistics, and mathematical modelling? Would you like to develop new methods for uncertainty
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application! We are looking for a PhD student in Medical Science, AI and Bioinformatics. Your work assignments This project aims to develop AI foundation models for integrative single-cell and multi-omics
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.): Research within hydrometallurgy, redox–dissolution chemistry, battery recycling, and data-driven modelling Develop and apply mechanistic and data-driven models to identify reaction regimes and predict
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application! We are looking for a PhD student in Medical Science, AI and Bioinformatics. Your work assignments This project aims to develop AI foundation models for integrative single-cell and multi-omics
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candidate will join the Scientific Machine Learning group at TDB and SciLifeLab. The group develops theory, methods and software for data-driven science, with a current focus on uncertainty quantification
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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through a model-driven approach, i.e. a combination of simulation- and data-driven methods and tools with data analysis and machine learning as an important part. The work builds on established theories and
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research environments in Computational Science, the research and education has a unique breadth, with large activities in areas such as numerical analysis, mathematical modelling, development and analysis
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directions: Long-term Autonomy in Uncertain Environments a. Agentic Planning and Reasoning - Semantic Mission Planning with Foundation Models - Foundation models based task decomposition - Event-driven task re
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, biofilm formation and resistance evolution in a defined four-species UTI model. The project combines longitudinal experiments in planktonic and biofilm systems with quantitative analysis. The work includes