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Field
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knowledge of statistics (R) Experience with multiverse analysis and open science practices Experience in the measurement and evaluation of eye tracking data is desirable Experience with physiological data
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diverse soil and management conditions - Excellent technical knowledge of nitrogen dynamics and loss pathways in crop production - Proficiency in GIS and remote sensing workflows, using tools like QGIS, R
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. Exposure to conducting evidence synthesis and systematic reviews. Experience and working knowledge of at least one statistical software (E.g. SAS, STATA, R, and SPSS). Preferred Qualifications Work
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or disease modeling in R and/or Python statistics data analysis communication (written and verbal) This does not mean you need expertise in these areas but rather that you have some base knowledge upon which
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(e.g., Bioconductor, Galaxy, KEGG, Reactome, STRING). Proficiency in Python, R, and Unix/Linux-based environments for high-performance data analysis. Knowledge of biological network inference, causal
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
classifiers). Proficiency in programming languages such as Python, R, and experience with bioinformatics pipelines. A proven track record of scientific publications in metabolomics, AI, or computational biology
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meet the essential criteria set out above will not be able to book) To apply today, please visit:https://forms.office.com/r/EBjJpSsQJY Deadline midnight, August 28,however, candidates are encouraged
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in population genetics, statistical genetics, or a closely related area. Proficiency in statistical and bioinformatics tools and programming languages (e.g., Hail, R, Python). Experience with
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learn new advanced analysis techniques (e.g., in Matlab, R, or Python) if relevant for the task. Write up research results in the form of journal articles. Participate in and co-arrange national and
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publications in peer-reviewed journals, demonstrating a commitment to scientific excellence and innovation. Experience with data analysis pipelines, programming (e.g., Python, R), and bioinformatics software