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applications in parametric modeling environments, including beam, shell, and solid-based elements. Creating a robust foundation in FEM theory and numerical methods, enabling the candidate to specialize in
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Cookie-erklæringen var sist oppdatert 14.06.2025 Hva er en cookie? En cookie er en liten datafil som lagres på datamaskinen, nettbrettet eller mobiltelefonen din. En cookie er ikke et program som kan
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3,750 students and 455 employees. The PhD specialisation NHH is pleased to announce vacancies at the Department of Business and Management Science. Candidates admitted to the PhD programme will receive
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of teaching and administrative duties (up to 25 %), depending on the competence of the successful applicant and the needs of the department. The research fellow must take part in the Department’s PhD program
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on theory, methods and applications. The areas represented include: fluid mechanics, biomechanics, statistics and data science, computational mathematics, combinatorics, partial differential equations
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a single method for anisotropic flow modelling for both ice and olivine, by mapping CPO parameters directly to anisotropic viscosity parameters. This technique should reduce the computation complexity
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Ability to actively communicate and co-operate within a larger research team is required. Experience with LINUX environments and analysing large datasets from numerical models is an advantage Experience
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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
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have expertise in at least one of the following research areas: PDEs, numerical methods, optimization, functional analysis, or stochastic analysis Candidates without a master’s degree have until 1st
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starting the PhD). The candidate must be qualified for admission to the ph.d. program Strong background in quantitative methods (reflected in courses and/or research experience) Proficiency in R, Python