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should have a strong quantitative background, for example in statistics, mathematics, computer science, or a related field, very good programming skills, a demonstrated interest in statistical modelling
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biochemistry, using statistical programs such as R, SPSS, PLINK, or similar programming environments. Statistical methods include regression analyses, protein quantitative trait locus (pQTL) analyses
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). Practical experience of experimental spectroscopy or diffraction techniques such as XAS, XRD, FTIR, and XPS, of molecular modeling (MD/MC, DFT), and familiarity with basic programming (Python, MATLAB
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coursework in probability theory, programming, and linear algebra. be able to read and write mathematical proofs and cryptographic analyses. be proficient in academic English. For directions 1 and 3, it is
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programming experience in one or more languages such as Python, R, or MATLAB. Experience working with marine / environmental observation systems, sensor data, and / or remote sensing. Experience handling large
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microbiological laboratory methods; basic programming or bioinformatics; and clinical or biomedical data analysis. In the selection process, considerable emphasis will be placed on the applicant’s scientific