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or heterogeneous environmental datasets Familiarity with spatial analysis, GIS, or geospatial data workflows. Experience with machine learning, modelling, or systems analysis approaches Interest in resilience
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with European industry. The EISLAB division at Luleå University of Technology conducts research in electronic systems design, sensor systems, cyber-physical systems, the Internet of Things and machine learning
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robotics. Specific application areas of focus are long-term autonomous missions in large and uncertain environments, semantic mission planning with foundation models, agentic task decomposition and event
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. The EISLAB division at Luleå University of Technology conducts research in electronic systems design, sensor systems, cyber-physical systems, the Internet of Things and machine learning, and works on
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and theoretical work. You will learn how to collect and analyse data within your research area as well as communicate your results at national and international conferences and in scientific journals
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of software infrastructure to optimize data workflows Developing analytical methods to integrate different types of sequencing-based DNA data. Developing computational models for prognosis and treatment
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role in enabling this transition, while also introducing new challenges related to system dynamics, stability, and control. This project focuses on the development of modeling, stability analysis
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combine ultrafast pump–push–probe experiments with sub-10 fs resolution, finite-element simulations, and quantum models extending the Tavis–Cummings Hamiltonian. The aim is to demonstrate coherent control
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robotics. Specific application areas of focus are long-term autonomous missions in large and uncertain environments, semantic mission planning with foundation models, agentic task decomposition and event
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of engineered underground hydrogen storage in lined rock caverns (LRCs) excavated in hard crystalline rock. Your tasks are to: - develop coupled thermo-hydro-mechanical numerical models to simulate hydrogen