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Field
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and sensor systems for remote maintenance and reliable fusion operations. Artificial Intelligence Developing advanced artificial intelligence/machine learning (AI/ML) solutions for fusion science and
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will be advantageous. Knowledge of machine learning or reinforcement learning techniques will be advantageous. Proficiency in algorithm development using Python will be advantageous
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journals and conferences such as Journal of Machine Learning Research (JMLR), Transactions on Machine Learning Research (TMLR), NeurIPS, ICML, RLDM, ICLR, IROS, or other top IEEE venues. Experience with
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large, highly diverse and multi-modal datasets (e.g., images, surveys, statistical and sensor data). Familiarity with geostatistical, GDAL, Python, PostGIS/PostgresSQL, Machine Learning, AI, Internet
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Norwegian courses. Required selection criteria You must have completed a doctoral degree in (machine learning, statistics, or similar). You must have a professionally relevant background in algorithms
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About the Opportunity About the Institute Do you want to be part of an exciting new Institute focused on combining human and machine intelligence into working AI solutions? We are launching a
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, integrating the outcomes to inform future projected trend analysis. Applying statistical and machine learning to project future data analysis. Managing and analysing large data sets using efficient data
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policy relevance. Coordinate modelling activities across multiple projects and deliver high-quality outputs on time. Integrate new methodologies, including AI and machine-learning approaches
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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completed a doctoral degree in (machine learning, statistics, or similar). You must have a professionally relevant background in algorithms, machine learning, database systems, or data mining. Experience with