Scientist II, Clinical Bioinformatics
About The Position
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.
Requirements
- 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.
Nice To Haves
- 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
Responsibilities
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
Number of Employees
1,001-5,000 employees
