121 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions in Norway
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- University of Oslo
- NTNU Norwegian University of Science and Technology
- NTNU - Norwegian University of Science and Technology
- UiT The Arctic University of Norway
- University of Bergen
- University of Stavanger
- Western Norway University of Applied Sciences
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- NORCE Norwegian Research Centre
- Norwegian University of Life Sciences (NMBU)
- OsloMet - storbyuniversitetet
- OsloMet – Oslo Metropolitan University
- Peace Research Institute, Oslo (PRIO)
- Simula UiB
- The Peace Research Institute Oslo (PRIO)
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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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Fellow will acquire. Access to career guidance will be provided throughout the doctoral education. The University of Stavanger funds the position. It is connected to the international research project
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collaborations across Norwegian universities, research institutes, industry, public agencies, and leading global institutions. We welcome motivated applicants in robotics, control, AI, machine learning, physics
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, and environmental changes, such as climate change, biodiversity loss, and pollution, and the effects of new policies. Teach two courses per academic year at Bachelor or Master levels and supervision
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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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calculations Knowledge about machine learning application in condensed matter Knowledge about magnetism, superconductivity, and topological order Personal characteristics We are looking for a candidate who is
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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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mixed models, permutational methods, Bayesian analyses, machine learning algorithms, structural equation modeling). A good practical knowledge of R Personal characteristics To complete a doctoral degree
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of partial differential equations (PDE). Examples of models in the scope of the project include particle models, stochastic PDE and models from fluid dynamics and machine learning. What skills are important in
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analysis, machine learning, and interactive and collaborative systems. The prospective PhD candidate will work in close cooperation with staff and our current PhD students. PhD research fellows receive