Computational Genomics, Statistical Bioinformatics Expert (PhD)

Apply advanced computational genomics and statistical bioinformatics expertise to realistic, multi-step scientific data analysis projects spanning quantitative biology and translational biomedicine. Key Responsibilities

• Independently inspect biological and biomedical datasets, perform quality control and exploratory analyses, select appropriate statistical methods, and carry out analyses in R and Python.
• Navigate ambiguous research workflows by identifying key analytical decisions, possible confounders, and limitations in available data.
• Use scientific software, code, and command-line tools to create reproducible analyses and structured final outputs.
• Interpret findings in relation to the underlying biological or translational question, clearly communicating assumptions, uncertainty, and conclusions.
• Collaborate with a multidisciplinary team of scientists and AI research specialists.

• 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, particularly 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 knowledge of statistical modeling, experimental design, quality control, and scientific inference.
• Experience independently completing multi-step computational research workflows, from raw or messy data through final interpretation.
• Clear scientific writing skills and the ability to document methods, assumptions, and results precisely.
• Familiarity with reproducible research practices, such as notebooks, scripts, version control, or workflow tools, is a plus.

• Remote, hourly, project-based engagement.
• Open to qualified experts worldwide.

120 hourly.