50 parallel-computing-numerical-methods Fellowship research jobs at University of Bergen
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on developing and implementing novel computational methods and apply these in the pursuit of fundamental biological questions. The PhD candidate will benefit from membership of the new Norwegian
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for computational science. It is an advantage for applicants to have experience with mathematical modeling and numerical methods for thermal compositional multiphase flow, phase separation, and reactive transport in
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of numerical optimization is an advantage. Experience from high-performance computing is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good collaborative
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foundation from numerical and functional analysis Build on the literature related to linear operator preconditioning and nonlinear preconditioners for Newton methods Use concrete model problems and numerical
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positions are closely linked, and candidates will have the opportunity to collaborate together and learn methods from the parallel project, building a broad skillset. Both positions are part of the larger
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opportunity to collaborate together and learn methods from the parallel project, building a broad skillset. Both positions are part of the larger project “Bringing the wild into the lab with Virtual Reality
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numerically implements the newly derived theoretical frameworks using fundamental computer programming languages. The numerical solver will leverage existing modules (by then) developed from the ‘OceanCoupling
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will conduct basic research supporting technology development in partner companies. The work includes combined use of mathematical, numerical, and experimental methods. Qualifications and personal
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additional collaborators including Prof. Alexander Babanin (University of Melbourne, Australia), will form a team of supervisors for the PhD fellow. The research will involve running customized numerical
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the use of modern machine‑learning methods within applied mathematics—particularly physics‑informed learning, anomaly detection, data‑driven modelling, and the construction of surrogate models grounded in