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these challenges by advancing machine learning (ML)-based and data-intensive methods for the scalable design, processing, and deployment of DPPs. The advertised PhD position focuses on developing ML-based and
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English English PhD Research Fellow in Machine Learning and Distributed Data Processing Apply for this job See advertisement Job description Position as PhD Research Fellow in Machine Learning and
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PhD Research Fellow in ML-assisted reservoir characterization/modelling for CO2 storage (ref 290702)
-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 candidate with a strong
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(PDE). Examples of models in the scope of the project include particle models, stochastic PDE and models from fluid dynamics and machine learning. Place of work is the Department of Mathematics, Blindern
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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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. • Experience with machine learning and artificial intelligence. • Strong programming skills (e.g., Python, C++), and familiarity with ROS or similar frameworks. • Experience with simulation tools like
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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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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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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