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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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variables, fixed effects for panel data, matching estimators, or machine learning) or other advanced statistical modelling.- Advanced programming skills in Stata, R, Python or a similar software.- Strong
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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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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
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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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in modelling using Matlab or Python. You have solid experience using process simulator AspenPlus or Hysys, and you have used them to simulate absorption processes. You have experience with absorption
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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