- You have a PhD in Computational Biology, Bioinformatics or a related field. Alternatively, you have a PhD in Molecular Biology, Immunology, or a similar field with a strong hands-on bioinformatics component. Furthermore, postdoctoral training or industry experience is expected.
- Strong background in oncology and immunology is highly preferred.
- You have demonstrated success via first or senior author publications in peer-reviewed journals, both from graduate and postdoctoral work.
- You have strong experience in NGS and other ‘omics data analysis (for example, bulk or single-cell RNA-seq, TCR-seq, ATAC-seq, whole-exome sequencing, etc.).
- Practical understanding of statistical principles relating to high-dimensional data analysis, such as gene expression analysis in large cohorts.
- You are fluent in R and/or Python, both for data analysis and for developing code packages or modules for computational pipelines.
- You have experience with high performance compute clusters and cloud environments, as well as modern tools for collaborative coding and data analysis (e.g., git, JIRA, Confluence, Rmarkdown or Jupyter Notebook, etc).