Sr. Scientist, Clinical Bioinformatics

10x Genomics•Pleasanton, CA

About The Position

10x Genomics is establishing a diagnostics effort, translating our leading single-cell and spatial assay technologies into impactful clinical applications. We are seeking a Senior Scientist to join the clinical bioinformatics team. The ideal candidate excels at distilling complex biological questions into actionable computational strategies, implementing computational/statistical methods with robust software development practices and applying them to large-scale single-cell or spatial transcriptomics datasets to derive clinically meaningful insights. The role requires statistical and software development rigor, proficiency with large-scale bioinformatics analyses and strong scientific acumen. 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.
5+ years of industry experience after Ph.D
In-depth understanding of the assumptions, limitations and caveats of statistical methods.
Experience developing and optimizing high-performance, scalable code.
Experience analyzing large-scale single-cell or spatial transcriptomics datasets to derive biologically meaningful insights and/or diagnostic biomarkers.
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 in-situ or single-cell transcriptomics technologies is a strong preference
Development of statistical models and algorithms for spatial or single-cell transcriptomics data
Creative and thoughtful application of machine learning and AI, 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
Hands-on research experience in cancer research/oncology
Knowledge of clinical genomics, biomarker discovery and diagnostics

Responsibilities

Implement rigorous computational/statistical methods for single-cell and spatial transcriptomics data analysis.
Implement and maintain bioinformatics packages and pipelines for reproducible, large-scale data processing.
Design, implement and validate biomarker scores for diagnostic applications.
Process and analyze single-cell or in-situ spatial transcriptomics datasets spanning hundreds to thousands of samples.
Derive actionable insights from clinical/translational single-cell or in-situ spatial datasets.