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. The project is conducted in close collaboration with the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation until 2033
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extensive knowledge on zooplankton imaging techniques ability to program and train machine learning models for automated image classification experience with shipborne campaigns and ready to join multi-week
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health. Visit https://www.umu.se/forskning/grupper/interactive-and-intelligent-systems/ for more information. Project description and work tasks We are seeking a candidate for a 3-year postdoc position
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, postdocs, students, and collaborators. Support postdoctoral lifecycle activities, including onboarding coordination and administrative updates. Assist with planning and executing the division's weekly
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members of the group help each other. Opportunity for growth as a software developer in areas such as CUDA programming, analysis of neural data, machine learning model applications, and real-time
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also will participate in weekly seminars with other Active Learning Initiative postdocs, receiving training and support in designing and implementing research-based teaching strategies. The Postdoctoral
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on advanced machine learning and emulation approaches. Key responsibilities: The candidates will be expected to work on the following tasks: - Develop machine learning (ML) methodologies appropriate
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separation on commercial recordings and extracting audio features (onsets, pitch, harmony, dynamics); curating datasets; and integrating machine learning approaches to complement rule-based methods. For more
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systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning
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structure and quantum chromodynamics, 2) Experience in the use of machine learning and high-performance numerical computations, 3) Readiness to teach courses in physics and computer science in English