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technologies that are commonly used in the group include Python, Fortran, high-performance computing, MPI, OpenMP, Commander, Git, and Latex. Familiarity with these concepts will be an asset, but are not
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following computing skills will be considered an advantage: Natural Language Processing and LLMs; R; Python. Applicants must be fluent in English. Applicants who have completed their education outside
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, MATLAB, Python) background in process safety, thermal system design, or energy storage is considered an advantage skills in technical writing, scientific publications and presentations a good command of
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the Norwegian educational system Experience with high-throughput sequencing omics data analysis Proficiency in programming with Python, R, or C++ Candidates without a master’s degree have until 31 August 2025
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(IRT) models in small samples. The ideal candidate has prior knowledge of IRT models, a basic understanding of common estimation methods, and strong programming skills in R, Python, or another relevant
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. Documented experience with Bayesian spatiotemporal modelling, including experience with the INLA framework for Bayesian inference Documented experience with programming in either Python or R. Foreign completed
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on MATLAB, Python, Julia, Javascript, DigiSilent Power Factory. Possesses a strong academic record, with relevant experience in either industry or academia, and can show experience from paper publishing. Has
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the master's degree has been awarded. The candidate must have good knowledge in atmospheric dynamics. Proficiency in scientific coding and data analysis (e.g., Python, MATLAB, R, C++, FORTRAN) is required
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relevant for the research program outlined above with a strong background in nuclear structure physics of exotic nuclei Expertise in scientific computing, including proficiency in C++ or Python programming
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experience coding within Unix-based HPC environments, and a background in MATLAB and Python programming languages would suit working with our existing code base Emphasis is also given to personal suitability