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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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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 to complete the final exam
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for Bayesian inference Documented experience with programming in either Python or R. Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system Fluent
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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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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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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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Expertise in scientific computing, including proficiency in C++ or Python programming Fluent oral and written communication skills in English Desired qualifications: It will be an advantage that candidates
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for appointment. Good knowledge of programming and data analysis using Fortran, Matlab, Python, or similar programming languages. Experience in using and developing models to simulate natural systems. Knowledge
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an approved doctoral thesis and public defense are eligible for appointment. Good knowledge of programming and data analysis using Fortran, Matlab, Python, or similar programming languages. Experience in using
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Language Processing and LLMs; R; Python. Applicants must be fluent in English. Applicants who have completed their education outside of the EU/EEA-area and who do not have English as a native language, must document