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You must meet the requirements for admission to the faculty's Doctoral Programme Software skills in 2D/3D technical drawing Strong theoretical background in fluid mechanics, mathematics and physics
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Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience in quantitative statistical analysis and epidemiology Familiarity with statistical software such as SPSS, STATA
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Experience in statistical analysis using SPSS, Stata, R, Phyton, or equivalent software Authorship of scientific publications Personal characteristics Ability to work both independently and as part of a team
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Doctoral Programme - PhD - Faculty of Engineering Science - NTNU You must have prominent skills in using GIS software (such as QGIS or ArcGIS Pro) and be comfortable working with large datasets. You must be
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in English Solid knowledge in finite element analysis (FEA) and strong skills in FEA software such as ABAQUS Hands-on experience in the construction and application of deep learning neural networks
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of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Strong skills in programming languages and software-engineering paradigms, e.g. Python; OOA/OOD/OOP
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analysis (FEA) and strong skills in FEA software such as ABAQUS Hands-on experience in the construction and application of deep learning neural networks on material design by using PyTorch or Matlab PLEASE
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element methods. Knowledge of aluminium alloys Experience using non-linear finite element software, e.g., Abaqus. Experience with programming using Python and Fortran. Experience with conducting
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. Specific experience with Rifts, Rifted Margins and Interpretation of seismic reflection data, using modern seismic interpretation software such as Petrel. You must have a relevant Master's degree in Geology