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treatment. Develop methods and models that can predict the course of the disease by analyzing detailed data on the immune system and metabolism. We are conducting a large study, the CoVUm study, involving 579
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researcher to join our research group for two years (https://dbojar.com/bojar-lab/ ). The successful candidate will perform biochemistry assays, protein engineering, AI, and data science to predict protein
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(ACL) and other knee-related injuries. You will integrate and analyze large-scale clinical registry data in close collaboration with Sahlgrenska University Hospital, aiming to create predictive
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Battery Systems as well as the COMPEL partners. The aim of the postdoctoral project is to develop next generation simulation methodology to predict thermal runaway on the cell level. The combustion and gas
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integrate and analyze large-scale clinical registry data in close collaboration with Sahlgrenska University Hospital, aiming to create predictive, interpretable, and clinically actionable models
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integrate model-driven engineering approaches to support reconfigurable system architectures. -Implement and validate decision-support tools for energy-aware planning, predictive maintenance, and resource
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. Project description Holistic understanding of the interactions between climate, productivity, and organic matter decay, will be key for better climate predictions. This project focuses on a long term (~10
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lab is dedicated to advancing predictable and robust systems for protein production, purification, and detection. Our research spans protein engineering for therapeutic development, diagnostics, and
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to predict thermal runaway on the cell level. The combustion and gas model developed on the cell level will then feed into the work to accurately predict thermal runaway on pack, module, and system levels
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and glycoproteomics. Computationally, they will engage in the analysis of various ‘omics data, be involved in using and improving AI models for glycan structure prediction, and perform biosynthetic