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tools and “big data” approaches with a special focus on Bayesian analysis Designing, conducting, and interpreting statistical analysis, including analysis of cohort, cross-sectional and clinical studies
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and statistical modelling approaches to extract meaningful patterns and predictive biomarkers from large-scale omics datasets. Contribute to the design and execution of research projects, including
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is expected An excellent mathematical background and experience in software development is required Experience in developing and applying statistical and/or machine learning-based computational methods
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Research Engineer (f/m/d) Background: Reproducible science requires access to suitable and transparent research software. In the field of luminescence-based chronology, the statistical programming
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Python language is highly recommended Previous experience in NGS data like metagenomics and transcriptomics analyses would be highly appreciated A good understanding of the statistical methods for multi
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with MS office, graphic programs, statistical software, bioinformatics tools and online tools (e.g. Illustrator, ImageJ, GraphPad Prism, R, BLAST) Fluent both in written and spoken English language We
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Broad knowledge with ADOBE/COREL DRAW graphic programs, statistical software and bioinformatics online tools (PRISM, TRANSFAC, CLUSTAL, BLAST, etc) English (written and spoken) for publication work
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sets and developing prediction tools based on traditional structured database tools and “big data” approaches with a special focus on Bayesian analysis Designing, conducting, and interpreting statistical
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. Prerequisites Doctoral degree with quantitative training or research experience Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software
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degree in a health-related subject is not required to apply Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software package Good