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/mathematical-cognition-and-literacy . The group collaborates with national and international experts in mathematical cognition, mathematics education, linguistics, and machine learning. Your immediate leader
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, Machine Learning, Complex Systems Modelling, Space Physics, and Ultrasound, Microwaves, and Optics. The department provides education at the Bachelor, Master, and PhD levels. Contact For further information
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important for renewable energy production and production variability will be an advantage. Knowledge of machine learning or optimization will be an advantage. Applicants must be able to work independently and
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computing language. Experience with machine learning methods is a plus. The research fellow must take part in the faculty’s approved PhD program and is expected to complete the project within the set
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degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system is required. The candidate must have interest and solid background in software systems, machine learning
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mathematical modelling tools. Excellent knowledge of programming languages such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in
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, sensor networks and measurement technology, grid computing and physics data analysis, machine learning, and interactive and collaborative systems. The prospective PhD candidate will be part of a research
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project/work tasks: The SnowAI project aims to use to produce new high-resolution datasets on snow depth in Western Norway derived from machine learning and radar remote sensing. The successful PhD
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Postdoctoral Research Fellow in Ethics and AI Apply for this job See advertisement About the position Integreat – Norwegian Centre for Knowledge-driven Machine Learning at University of Oslo is looking for a
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-compliance in ecological momentary assessment, or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models in small samples. The ideal candidate has prior