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) techniques applied to geological materials (e.g., EBSD, FIB-SEM, EDS, STEM imaging) Computational skills (e.g. Matlab, Python) Previous experience, at the PhD level, in one of the following fields: (1
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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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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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programme may be given consideration. The suitable candidate must have: Strong programming skills (preferably Python or MATLAB) Experience with using satellite remote sensing data (ideally for polar
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Penetrating Radar Near Surface Geophysics Operation of planetary science instruments The Post Doc candidate must have experience in Python programming The Post Doc candidate must be eligible to be able to join
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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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/quantitative research methods Documented programming experience for example GitHub project on MATLAB, Python, Julia, Javascript Possesses a strong academic record, with relevant experience in either industry
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, programming, systems thinking, and qualitative/quantitative research methods. Documented programming experience for example GitHub project on MATLAB, Python, Julia, Javascript. Experience in mathematical
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analysis using Matlab, Python, or similar programming languages. Good experience in inorganic material characterization with standard techniques such as SEM-EDX, XRD, Raman, FTIR. The candidate is expected