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opportunity for career development for a hard-working candidate. Main responsibilities Develop and apply machine learning and statistical modeling techniques, including novel AI architectures, for the analysis
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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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. 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 background in one or more of the fields of rock physics
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both on the sequence and structural level, developing and employing machine-learning tools for predicting antibody-epitope binding. In silico antibody design is a long-standing computational and
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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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Norwegian security clearance Candidates without a master’s degree have until 1st of July 2025 to complete the final exam. Desired qualifications: Experience in areas such as machine learning, computer vision
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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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for Knowledge-driven Machine Learning. We are looking for a motivated candidate, who has interest in both theoretical, methodological and applied research in anomaly detection in sequential data settings, and who
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measurement quality issues related to respondent non-compliance in ecological momentary assessment or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models
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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