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Languages English English English Researcher in machine learning modeling of human physiological models Apply for this job See advertisement About the position Position as Researcher available at the Center
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well as candidates with a background in machine learning methods. The PhD programme will straddle the boundaries between the field of wave modelling and the general field of machine learning, and we will set up a team
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”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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relevant background within control, building, or HVAC engineering. A background in applied mathematics can also be relevant if there is a strong focus on data-driven modeling, machine learning, and control
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relevant experience in the development and deployment of machine/deep learning models as well as the use of remote sensing data You must have relevant experience in the development of hydrodynamic and water
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Experience in computational cardiovascular biomechanics Experience in medical image segmentation Experience in Python programming or a similar programming language Experience with machine learning models Good
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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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centered around a unique, open-source digital platform enriched with data and powered by domain knowledge-based advanced machine learning and artificial intelligence capabilities. By introducing a Digital
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. Special focus will be devoted to the interpretability of the predictions and to the use of physical models in combination with machine learning techniques. You will work alongside other highly motivated and
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using machine learning or any other AI technique. Knowledge of CCS. Good oral and written presentation skills in Norwegian/Scandinavian language equivalent level B2. Personal characteristics To complete a