About this role
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
Skills
Computational GenomicsBioinformaticsStatistics
Sourced from Mercor · original listing · application link last checked 24 Aug 2026