Descripción del trabajo### What you’ll do - Complete realistic, multi-step scientific data-analysis tasks in computational genomics, quantitative biology, and translational biomedicine - Independently inspect datasets, perform quality control and exploratory analysis, select appropriate statistical methods, and execute analyses in R and Python - Navigate ambiguous research workflows by identifying key analytical decisions, potential confounders, and limitations in the available data - Use scientific software, code, and command-line tools to generate reproducible analyses and structured final outputs - Interpret results in the context of the underlying biological or translational question, clearly communicating assumptions, uncertainty, and conclusions - Work with a multidisciplinary team of scientists and AI research specialists ### Who we’re looking for - PhD in computational biology, bioinformatics, statistical genetics, quantitative biology, biostatistics, genomics, or a closely related field - Deep, hands-on experience analyzing biological or biomedical data, especially genomics, sequencing, single-cell, population-genetics, QTL/GWAS, or related omics datasets - Professional fluency in **R and Python**, including the ability to write, debug, and explain analysis code - Strong foundation in statistical modeling, experimental design, quality control, and scientific inference - Experience independently carrying out multi-step computational research workflows from raw or messy data through final interpretation - Clear scientific writing and the ability to document methods, assumptions, and results precisely - Familiarity with reproducible research practices, including notebooks, scripts, version control, or workflow tools, is a plus ### Details - Project-based engagement with competitive, expertise-based pay - Open to qualified experts globally