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complex or high-dimensional systems. Experience with physics-informed or constraint-based machine learning (e.g. neural ODEs, energy-based models) Experience with dynamical systems, stochastic processes
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models for complex data, including temporal data. We are interested in both data-driven models as well as models built from synthetic data. Within privacy, we are interested in different types of privacy
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for acquiring, managing, analyzing, modelling, and visualizing geographic information to understand spatial patterns, processes, and relationships. Lund University GIS Centre at the Department of Earth and
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. Subject description Automatic Control comprises the analysis and synthesis of models and model-based algorithms for control, estimation, and monitoring of complex dynamic systems. Project description
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modelling, geospatial data science, generative modelling, mobility data analysis, or transport simulation, especially when combined with knowledge of complex systems, network science, resilience theory, urban
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expertise at the interface of biology and quantitative science. The project is particularly suitable for candidates interested in evolutionary theory, biological complexity, mathematical modeling, and the
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of Technology’s campus in Luleå. Subject description Automatic Control comprises the analysis and synthesis of models and model-based algorithms for control, estimation, and monitoring of complex dynamic systems
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complex functions. By equipping immune cells with new generations of synthetic receptors, we develop and evaluate strategies to enhance their ability to recognize, seek out, and eliminate malignant cells
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models for complex data, including temporal data. We are interested in both data-driven models as well as models built from synthetic data. Within privacy, we are interested in different types of privacy
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‑solving with creativity and critical thinking. Personal skills Proficient in complex analytical methods, e.g. transport/energy/health forecasting and simulation models. Has teaching and supervision