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the applicant to take an active role in applying advanced imaging methods for processing and evaluating PET, MRI imaging data, performing statistical analyses, and preparing scientific manuscripts under
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biological techniques. Documented experience in analyzing biological samples with LC-MS/MS is required. Previous experience in affinity purification and good analytical and statistical skills, as
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earlier. To be eligible, the applicant must have: A doctoral degree in medical epidemiology or an equivalent field. A formal education in statistics and epidemiology. Experience in handling large register
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or biostatistics and experience in epidemiological research. The successful applicant has a high level of proficiency in statistical methods applicable to epidemiology and be an independent user of statistical
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This project requires strong skills in quantitative methods and experience in statistical programming, mainly in R. The project uses open science practices as far as possible, thus, a proven track record of open
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multidisciplinary team · Excellent organization skills and attention to detail · Advanced skills in at least one statistical software (R, SAS or Stata) · Excellent written and oral communication skills · Fluent in
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ability to integrate information from multiple molecular levels and anatomical locations both to improve the statistical power of detecting and defining molecularly distinct sub-groups in small patient
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for each specialist area below. (i) Computational Biology Required Expertise working with big data (generated by e.g. scRNAseq and miRNAseq). In-depth knowledge of statistical methods to analyze non-standard
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either required or meritous for each specialist area below (i) Computational Biology Required Expertise working with big data (generated by e.g. scRNAseq and miRNAseq). In-depth knowledge of statistical