About The Role
10x Genomics is establishing a diagnostics effort, translating our leading single-cell and spatial assay technologies into impactful clinical applications. We are seeking a Scientist II to join the clinical bioinformatics team. The ideal candidate excels at distilling complex biological questions into actionable computational strategies, implementing computational/statistical methods and applying them to large-scale single-cell or spatial transcriptomics datasets to derive clinically meaningful insights.
The role requires a biology-first mindset, proficiency with large-scale bioinformatics analyses, strong scientific acumen and statistical rigor. The successful candidate will have an opportunity to work with some of the largest biomedical datasets assayed using cutting-edge 10x Genomics technologies, deriving clinical insights that power the next generation of clinical diagnostics.
What You Will Be Doing
• Implement rigorous computational/statistical methods for single-cell and spatial transcriptomics data analysis. • Derive actionable insights from clinical/translational single-cell or in-situ spatial datasets. • Design, implement and validate biomarkers for diagnostic applications. • Implement and maintain bioinformatics pipelines for reproducible, large-scale data processing. • Process and analyze single-cell or in-situ spatial transcriptomics datasets spanning hundreds to thousands of samples.
To Be Successful, You Will Need
Ph.D. in bioinformatics, computational biology, genomics or a related discipline with extensive hands-on experience in single-cell NGS data analysis. A minimum of 2 years of industry experience post Ph.D. Experience analyzing large-scale single-cell or spatial transcriptomics datasets to derive biologically meaningful insights and/or diagnostic biomarkers. In-depth understanding of the assumptions, limitations and caveats of statistical methods. Experience developing and optimizing high-performance, scalable code. Proficiency working in a Linux environment. Goal-oriented, self-motivated and an independent problem solver. Meticulous attention to detail and a conscientious work ethic.
Preferred Skills
• Hands-on experience with 10x Genomics single-cell and in-situ transcriptomics technologies is a strong preference. • Hands-on research experience in cancer or autoimmune diseases is a strong preference. • Knowledge of clinical genomics, biomarker discovery and diagnostics. • Development of statistical models and algorithms for single-cell or spatial transcriptomics data. • Application of machine learning, particularly in the context of genomics. • Proficiency with workflow orchestration frameworks such as Snakemake, Nextflow or Martian. • Programming best practices including data analysis reproducibility, version control, design patterns, testing, debugging and profiling. • Track record of writing production-level code or maintaining published software packages. • High-throughput computing infrastructure such as HPCs or cloud computing.