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for this position. Applicants should be proficient in R, Python, or equivalent statistical software. Some background knowledge in either (computational) Bayesian methods, or statistical learning for molecular data
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requirements for admission to the faculty's Doctoral Programme You must have good written and oral English language skills Experience with programming in Python or similar languages
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) for general criteria for the position. Preferred selection criteria Background in programming (Matlab, python, …), familiar with Multi-body dynamic tools and good knowledge of statistics will be an advantage
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background in programming (ex. Python/Julia/Matlab). Excellent written and oral English. The appointment is to be made in accordance with Regulations for the Universities and Colleges Act (university and
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Science, Atmospheric Science, Environmental Science, or related fields · Good knowledge and skills in statistics and programming (e.g. R or Python) is required · Experience with data analysis related
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-based computational homogenization. Experience using non-linear finite element software, e.g., Abaqus. Experience with programming using Python and Fortran. Experience with conducting experimental work
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for the position. Preferred selection criteria Experience with modern statistical techniques using relevant scripting languages (R, python, bash, etc.) Experience with genomic library preparation Experience working
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OpenSees or similar) Programming skills (e.g. Matlab, Python or similar). Knowledge of European standards for the design of buildings (Eurocodes) Ability to handle big datasets Oral and written presentation
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programming skills in one of the following: Python, Matlab, C/C++. You must have Norwegian, Swedish, or Danish language skills corresponding to the scale A2 in the Common European Framework of Reference
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programming skills in relevant languages and in particular in Python Competency and experience in AI methods Good oral and written communication skills in English