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- NTNU Norwegian University of Science and Technology
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under the “Cryptographic elements of trustworthy AI” project. The main research objectives for the project are the following: Analyze security of Machine Learning (ML) models against data modifications
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methods may include physical models, multivariable analysis, self-diagnosis, and AI algorithms. Given the importance of long operating times for underwater sensors, energy-efficient processing is central to
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other PhD projects within SFI Smart Ocean. These methods may include physical models, multivariable analysis, self-diagnosis, and AI algorithms. Given the importance of long operating times for underwater
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://www.ntnu.edu/ept ) at the Norwegian University of Science and Technology (NTNU) is seeking a PhD candidate to work within process modeling and simulation of novel zero-emission oxy-fuel combustion CO2 capture
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, training deep learning models to adapt designs to boundary conditions, and integrating FEM workflows within parametric modeling environments like Grasshopper. The candidate will contribute to building a
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affecting the intestinal epithelium and the possible partners related to the different phases of the disease. The work will be a combination of ex vivo organoid cultures, in vivo disease models, combined with
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contribute to REGEL’s interdisciplinary work combining qualitative case studies, quantitative research, stakeholder engagement, and energy systems modelling. We are interested in applicants with a background
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outcomes. Computational biomechanical models of the MV will be developed to offer new insights, create mechanical markers for MR progression, and evaluate repair techniques through simulations. Despite
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winter CH4 emissions, using AI tools to develop upscaling tools or upscale to circumpolar region, or using climate modeling such as the Norwegian Earth System Model to constrain models and observations
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leader will be the Head of Department. About the project Modern control systems rely on being at least partially predictive while digital twins also must maintain a state model of the targeted cyber