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efforts to contribute to safer marine operations, we actively explore possibilities to utilize both numerical and machine learning methods to enhance the accuracy and resolution of metocean forecasts. About
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section. The PhD-position's main objective is to qualify for work in research positions. You will report to the head of Department. Duties of the position Developing numerical models to simulate the thermo
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combination of experimental testing, theoretical analysis, and numerical simulations, the study aims to characterize the effect of mechanical loading on surface oxide integrity and hydrogen permeation dynamics
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of experimental studies and numerical simulations.Identification and assessment of safety related issues during in-situ handling of the biocarbon may be done through methods like inspections
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Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine learning in general. OCBE has numerous collaborations with
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. ACS Nano 14 (8), 10562-10568 (2020) The visual appearances of disordered optical metasurfaces. Nature Materials 21, 1035–1041 (2022) Duties of the position Numerical simulations of plasmonic
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learning in general. OCBE has numerous collaborations with leading biomedical research groups in Norway and abroad. This therefore is a unique opportunity to contribute to cutting-edge research in statistics
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strong theoretical and numerical foundation in FEM, with applications in adaptive and performance-driven design. The work supports the broader goal of transforming how engineers and architects
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the gap between numerical simulations and clinical practice. The candidate will work alongside experts in solid mechanics, finite element analysis, and machine learning and cardiology, benefiting from
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methods to be considered for numerical optimization by an Energy and Emission Management System (EEMS). Data-driven AI methods (e.g. Reinforcement Learning and/or Recurrent Neural Networks) to be considered