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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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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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cycle processes, dynamics of oxygen and nutrient cycles, is required. Expertise in scientific scripting, programming, and data analysis (e.g., Python, Matlab, R) is required. Knowledge of climate
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data analyses Experience with rodent development, colonies maintenance Fluent oral and written English communication skills Python, Matlab, R or other relevant programming language skills Experience in
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development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Familiarity with software such as R or Python Some experience
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quality models, especially for coastal water environments You must be highly proficient in the use of programming languages including, but not limited to python, C++, but also database management
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techniques for screening plasmid libraries, such as phage display and yeast display is an advantage. Coding abilities in R/Python are an advantage. The candidate will work in a very ambitious interdisciplinary
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analysis). Skills in programming and scripting languages (Python/R/Matlab). A strong command of oral and written English. It is an advantage if you have Experience with cloud-based compute infrastructure
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-mechanical coupling. Understanding of wellbore and casing behavior under thermal load. Desired skills: Finite Element Analysis software: Abaqus, COMSOL Multiphysics, or ANSYS Python (for data analysis