36 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" Fellowship research jobs in Norway
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construction, and phylogenetic placement Ability to assess where machine-learning approaches may complement existing bioinformatic and phylogenomic methods, particularly for improving taxonomic resolution Skills
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cameras, heart rate monitors, and dedicated activity trackers for data collection and employ relevant machine learning methods for data analysis and sensor fusion. The PhD Research Fellow will collaborate
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, and the military. Both quantitative and qualitative approaches would be relevant, and comparative approaches (cross-sector, cross-institutional, cross-national, or other) are welcome, but not required
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Are you ready to take your research career to the next level? The Biopolymer NMR Group (https://folk.ntnu.no/aachmann/ ) is looking for a candidate to be hired for a least three-year postdoctoral position
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Sociology » Sociology of labour Sociology » Sociology of religion Sociology » Urban sociology Sociology » Other Educational sciences » Education Educational sciences » Learning studies Educational sciences
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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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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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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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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