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- NTNU Norwegian University of Science and Technology
- NTNU - Norwegian University of Science and Technology
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around three core scientific pillars—regenerative medicine, biomaterial science, and translational research models—SHIELD supports research on therapeutic strategies, novel antimicrobial materials, and
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metocean and biogeochemistry models accounting for climate change impacts across Europe (from the Nordic Seas to the Black Sea and Mediterranean Sea) and the Pan-Arctic region. The PhD project focuses on new
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access. The goals of such access include supporting registry operations as well as health care research. Of particular interest in this context are differentially private algorithms for statistical model
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. Its primary objectives are to: Improve understanding of intra-Draupne sandbodies to support more reliable reservoir modelling. Characterize reservoirs and seals. Develop innovative exploration
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and/or research experience in one or several of the following areas: methods and models related to power system protection and control or real-time systems and power system automation studies
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are differentially private algorithms for statistical model parameter estimation under different trust relations. About the project The position is funded by the Norwegian Research Center for AI Innovation and will be
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on childhood dementia CLN3, as part of ongoing research in the Bjørås group . About the project The current project is aiming at developing novel human models for childhood dementia CLN3 to recapitulate disease
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Hardware-in-the-loop testing) and control-in-the-loop testing will be an advantage. Experience with stability studies based on state-state modeling of power systems will be merited. Personal characteristics
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expertise in nonlinear model predictive control. Expertise in numerical optimal control. Personal characteristics To complete a doctoral degree (PhD), it is important that you are able to: Work independently
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data analysis workflow from data import/cleaning to descriptive statistics and at least one inferential model. Code must be included and clearly commented. This is required to demonstrate advanced