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. software and parallel computing is required. Skills in data processing and visualizing the results of quantum-chemical simulations are strongly desired. The candidates experienced in software
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are being strengthened. Subject and project description This project is focused on the development of high-fidelity reacting flow models to investigate thermal runaway in battery cells, pack, modules, and
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. The work involves areas such as AI-assisted automation engineering, digital twins, semantic modeling, secure data exchange, and reconfigurable production architectures. The research is carried out in
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focus on two main lines of research. The first concerns the modeling of general dark matter–electron interactions in detector materials. This will be achieved by combining methods from particle and solid
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to the development of methodologies for modelling, predicting, and validating dynamic interactions through numerical simulations and field measurements. This project is funded by The Swedish Transport Administration
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with industry, academia, authorities, and insurance companies. Main responsibilities Computational Modeling and Simulation Develop and validate finite element models using LS-DYNA, OpenRadioss
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on two main lines of research. The first concerns the modeling of general dark matter–electron interactions in detector materials. This will be achieved by combining methods from particle and solid state
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deviates from the classical asynchronous-irregular states (e.g. papers from the IBL). In this project we aim to characterize the statistics of both ongoing and task related activity and then build models
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focus is the interplay of these factors with mitochondrial translation systems and respiratory chain complex assembly. We use the yeast Saccharomyces cerevisiae as our primary research model. In
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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