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4th January 2026 Languages English Norsk Bokmål English English PhD Fellowship in Urban Morphology, Accessibility and Mobility Cultures Apply for this job See advertisement Job description The
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resulting precipitation and extreme weather. We study global and regional climate change and are at the core of international community climate modeling efforts that also involve AI and Machine Learning. We
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by integrating petrophysics, rock physics, geophysics, geomechanics and machine learning. A detailed project plan will be developed in collaboration with the successful candidate at the start of PhD
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of Anomalies ” (SODA), newly funded by the Norwegian Research Council and affiliated with Integreat – the Norwegian Centre for Knowledge-driven Machine Learning. We are looking for a motivated candidate, who
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, geometric deep learning. Considered an advantage: experience in programming or course work in computer science, algebra, topology or differential geometry, knowledge of topological data analysis or machine
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particle models, stochastic PDE and models from fluid dynamics and machine learning. What skills are important in this role? Qualification requirements: The Faculty of Mathematics and Natural Sciences has a
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or course work in computer science, algebra, topology or differential geometry, knowledge of topological data analysis or machine learning will also be a benefit. Qualifications and personal qualities
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engineering (elkraft). Experience in cybersecurity incident management. Experience in machine learning/artificial intelligence methods. Experience in simulation and modeling. Applicants will be assessed
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evolution, and pressure-build ups in potential multi-site storage licenses. The research will help to suggest best practices for machine learning integration in de-risking CO2 storage sites. We seek a
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: • Interest in evolutionary algorithms and optimization. Experience with quality-diversity methods is a plus. • Experience with machine learning and artificial intelligence. • Strong programming skills