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Field
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will be to: Model the optical, mechanical and optoelectronic properties of the fibers using ray tracing and finite element method models; Select and characterize soft materials for the fibers, and use
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
following areas: Large-deformation numerical modeling (e.g., Coupled Eulerian-Lagrangian (CEL), Material Point Method (MPM), or advanced Finite Element Methods). Physical modeling of tunnel excavation and
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: Task 1: Damage survey and mapping, based on the on-site surveys, and processing of the existing monitoring data. Task 2: Develop and calibration of a 3D numerical model, based on the Finite Element
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Norwegian). Desired qualifications Good experience/knowledge in electrical machines, synchronous generators, applied signal processing, applied mathematics, and finite element analysis. Programming experience
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mathematics, and finite element analysis. Programming experience in coding e.g. Python, or MATLAB Writing skills for research papers. Experience in applied machine learning, fault diagnosis, laboratory testing
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-source computational tools in a project that aims to create life-saving technology to prevent devastating skull fractures in elderly populations. This unique position combines advanced finite element
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by working to develop novel algorithms on finite element method, isogeometric analysis, geometric modeling, machine learning and digital twins to study various applications such as computational
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, 2025. We are looking for: The applicant should perform active research in numerical analysis of finite element or finite volume methods for coupled problems in one of the application areas of the group
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systems. Knowledge of simulation tools (e.g., Multiphysics finite element analysis, Matlab, Labview etc.) cleanroom experience, and characterization of electronic devices are required. Further, knowledge