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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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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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qualifications Crispr Crispr / siRNA screens Proficiency in programming (e.g., Python, R) Experience with high-throughput sequencing data analysis (e.g., CAGE, ATAC-seq, ChIP-seq, or Hi-C) Familiarity with
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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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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
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. Candidates experienced in atomic force microscopy and surface force apparatus techniques will be given a priority. Good knowledge of data analysis using Matlab, Python, or similar programming languages. Good
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in English Experience with programming (e.g. in MATLAB or Python) Desired qualifications: The ideal candidate should have: Demonstrated knowledge of fluid dynamics Experience with anisotropic viscous