10 algorithm-"University-of-Newcastle" Fellowship positions at University of Bergen in Norway
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the closing date for applications. The applicant must have good programming skills, excellent knowledge of algorithms, numerical methods, and signal processing Mandatory experience and formal training: signal
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the PhD has been awarded at the latest within 5 months after the closing date for applications. The applicant must have good programming skills, excellent knowledge of algorithms, numerical methods, and
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and application of fast solvers for Maxwell’s equations and nonlinear inversion algorithms that we have already developed in a previous PhD project. In addition to electromagnetic geophysics
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electromagnetic data during drilling. This includes the further development and application of fast solvers for Maxwell’s equations and nonlinear inversion algorithms that we have already developed in a previous
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collaborative skills. Applicants must be proficient in both written and oral English. Experience from one or several of the following areas is an advantage: Developing algorithms for CFD solvers (e.g. OpenFOAM
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advantage: Developing algorithms for CFD solvers (e.g. OpenFOAM). Programming in C++ or Fortran and proficiency with MATLAB or Python scripting. Experience with tools for simulating chemical kinetic, e.g
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at the University of Bergen. The Department hosts the Center for Digital Narrative (CDN) , a Norwegian Centre of Research Excellence. The Center focuses on algorithmic narrativity, new environments and materialities
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associated with the Center for Digital Narrative (CDN) , a Norwegian Center for Research Excellence. The Center focuses on algorithmic narrativity, new environments and materialities, and the shifting cultural
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Norwegian Center for Research Excellence. The Center focuses on algorithmic narrativity, new environments and materialities, and the shifting cultural contexts in which digital narratives are received and
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intermittent. The PhD will work will be twofold. The first part will be to improve and develop datasets and estimation algorithms for renewable energy that will enhance the simulation capabilities of the open