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-studies/. Background and description of tasks PhD project 1: The PhD project involves research using invertebrate model systems to investigate the mechanisms by which potential host genome editing processes
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flow behavior. The project also involves applying machine learning and computer vision techniques to enhance data analysis, pattern recognition, modeling, and prediction. The role requires a solid
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that lymphopenia is associated with decreased overall survival in cancer patients. Currently, there are no established methods that enable the modification of radiotherapy protocols to prevent lymphopenia without
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modeling molecular dynamics using our trapped Rydberg ion technology. This position is part of the ERC Synergy project "Open 2D Quantum Simulator (OPEN-2QS)", which start on 1 May 2025. The OPEN-2QS project
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analysis, modelling and field experiments, our project will illuminate the way forward for assisted migration (AM) as a pathway to sustain, and to restore in case of degradation, the biodiversity and
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to address critical issues related to the reliability and quality of large language models (LLMs) such as ChatGPT and Gemini. These models are increasingly used in essential sectors like healthcare, education
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holds a leading position in both research and education at all levels. We are currently Uppsala University's third largest department, with 350 employees, including 120 teachers and 120 PhD students
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equality and diversity as a strength and an asset. Description of the workplace InfraVis is Sweden’s national infrastructure for visualization of scientific data. Currently, InfraVis employs over 50 experts
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of Information Technology holds a leading position in both research and education at all levels. We are currently Uppsala University's third largest department, with 350 employees, including 120 teachers and 120 PhD students
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applications towards materials science. Generative machine learning models have emerged as a prominent approach to AI, with impressive performance in many application domains, including materials discovery