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Field
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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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genetics, and the ability to use R and/or UNIX/command line applications will be given preference. Pay and Benefits Pay Range: $58,656.00 - $61,008.00; depending on education/qualifications/experience Please
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of statistical programs (e.g. in Matlab, R or SPSS) German and English skills Proven ability to collaborate effectively, maintain performance under tight deadlines, and demonstrate a high level of commitment and
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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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Microsoft Word, Excel, Access and PowerPoint. Preferred Qualifications Proficiency and knowledge of multiple statistical software packages preferred, such as SPSS, SAS, R, Python, etc. Experience with ML/DL
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analysis software (e.g., SPSS, R, NVivo) is highly desirable. · Publication Record: Evidence of scholarly productivity, including publications in peer-reviewed journals. · Communication Skills: Strong
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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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due to climate change, as well as reservoirs, teleconnections, tipping points and fluxes of energy, water and carbon, while predicting future change. The CCI also addresses the R&D required to support
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, demonstrated experience of coding in programming languages such as R and Python is considered particularly advantageous. Examples of computationally intensive methods central to IAS and IDA are data-driven text