40 machine-learning-"https:" "https:" "https:" "https:" Fellowship positions in Norway
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/english/research/groups/dsb/index.html) as part of Visual Intelligence (http://visual-intelligence.no) , Norway's leading research centre in deep learning for image analysis. Starting date as soon as
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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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University of Stavanger invites applicants for a PhD Fellowship in in molecular modelling and machine learning for improved subsurface utilization, at the Faculty of Science and Technology, Department
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integration and optimized operation using machine learning and AI techniques as key drivers for improving system performance. The hired candidate will have the opportunity to work with cutting-edge energy
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of Visual Intelligence is to develop novel, innovative solutions based on deep learning to extract knowledge from complex image data. Deep learning, aided by machine learning techniques in general, has led
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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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viability data to discover new biomarkers and treatment strategies. You will work in a highly interdisciplinary environment spanning oncology, cell biology, imaging, bioinformatics and machine learning, with
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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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-working candidate. Main responsibilities Develop and apply machine learning and statistical modeling techniques, including novel AI architectures, for the analysis of complex traits and precision prediction
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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