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qualifications include a Master's degree in computational biology or a related field. Prior experience with programming, statistics and biomedical research is essential, while experience with machine learning is
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quantitative analysis. Experience with statistical modelling; familiarity with or interest in machine‑learning approaches is an advantage, but not a requirement. Excellent written and spoken English
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statistical modelling; familiarity with or interest in machine‑learning approaches is an advantage, but not a requirement. Excellent written and spoken English communication skills. A genuine interest in
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scientific publications in international peer-reviewed journals Experience in conducting empirical studies and knowledge of statistical data analysis (e.g., SPSS, R, Jamovi) Very good knowledge of Good
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collecting and analyzing survey data You took classes in statistics and econometrics, gained practical skills in this area (e.g., data analysis for your MSc thesis), and you seek to develop your skills further
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advanced statistical analysis, pathway & network analysis, Integrating complex clinical, biological and molecular data. Contributing to data visualization, figure generation and interpretation
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learning, AI, or statistical modeling applied to biological data Experience with genomics, transcriptomics, single-cell and/or spatial omics technologies Proficiency in scientific computing frameworks Strong
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15 Jan 2026 Job Information Organisation/Company Empa Research Field Computer science » Other Engineering » Other Mathematics » Applied mathematics Mathematics » Statistics Researcher Profile First
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. For both projects, skills in statistical data analyses are important. You enjoy engaging with ideas in depth and are motivated by understanding concepts rather than simply completing tasks. You are willing
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experience in managing plant growth facilities, in cultivating plants, microscopy, experimental design, statistical analysis and have knowledge on high-throughput image analysis, and hold a valid driver's