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- University of Oslo
- University of Bergen
- NTNU Norwegian University of Science and Technology
- UiT The Arctic University of Norway
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- NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU
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will also be encouraged to take part in the supervision of MSc and PhD candidates. You will be part of a larger project group across robotics, machine learning and health, and also interact with
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fields both locally (field by field) and regionally (groups of fields). Data driven analyses will be complemented by physical reservoir modelling, with machine learning approaches to extract correlations
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on the expertise of the seven research groups involved, using a combination of experiments in cellular and animal model systems, mathematical modelling, machine learning and music technology. One PhD student
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, mathematical modelling, machine learning and music technology. One PhD student or postdoctoral fellow will be recruited to each of these four fields and this group will work together on the AUTORHYTHM project in
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interaction processes and mineralogy or Physical and/or chemical planet formation processes Experience with numerical modelling of the relevant processes Interest in exploring statistical or machine-learning
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, progression, and disease heterogeneity. Among others, the group's current projects leverage approaches from network science and machine learning in tool development for (1) modeling of regulatory interactions
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previous experience in application of machine learning techniques within energy systems strong analytical skills and ability to collect, analyze and study the impact of low carbon technologies good knowledge
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science and machine learning in tool development for (1) modeling of regulatory interactions at bulk and single-cell resolution, (2) integration of regulatory networks with multi-omics data, (3) fine-tuned
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Experience with machine learning and statistical methods, especially in healthcare. Experience with federated learning. Knowledge about the health care system in Norway Good written and oral English and
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) to build library of spectra as a pathogen ID. Explore one of more of the following options: Explore use of machine learning and AI for classification of pathogens in co-operation with other team members