130 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)
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- The Peace Research Institute Oslo (PRIO)
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of GIS, spatial statistics, or other spatially relevant methods. Demonstrated experience applying machine learning and AI-based approaches to empirical disease, ecological, or biological datasets, with
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(PDE). Examples of models in the scope of the project include particle models, stochastic PDE and models from fluid dynamics and machine learning. Place of work is the Department of Mathematics, Blindern
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of AI and in particular machine learning (ML). As today’s mainstream AI/ML workloads often resort to large-scale and energy-hungry supercomputers, it is necessary have a more critical look at how HPC
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hazards, enhancing asset protection, maritime security, emergency preparedness, and societal resilience. The project will leverage advanced AI and machine learning techniques to enable predictive risk
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career development plans with formal supervision and project-based learning. Secondments, consortium meetings, and workshops will provide hands-on experience in collaborative modelling, scientific
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refractive-index imaging of complex samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue
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educational system. Strong background in molecular modeling, molecular dynamics simulations, or computer-aided drug design. Proven record of programming language through publicly available Github/Gitlab
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dynamics simulations, or computer-aided drug design. Proven record of programming language through publicly available Github/Gitlab or similar repositories. Experience in the cell biology lab Fluent oral and
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fish. Specifically, we have been working on salmon lice in commercial aquaculture. Current efforts use machine learning (object detection) to automatically quantify parasites in the sea, with ongoing
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kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several stakeholders: i) architects and urban