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bioinformatics, computer science, data science, or another relevant field experience in analyzing large biological datasets (e.g. genomics, transcriptomics, or proteomics) programming skills (e.g. R, Python
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methods (at minimum, linear regression (OLS) and logistic regression, as well as familiarity with some advanced methods). Proficiency with statistical software (e.g. R, Stata). Ability to work both
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to implement data analytics processes and algorithms in scientific programming languages (e.g., Python, R). The ability to collaborate within a multidisciplinary research group. Independent work, collaboration
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to implement data analytics workflows and algorithms using scientific programming languages (preferably Python but others like R, Julia or Rust can also do). Ability to cooperate with a multidisciplinary