Scientist II, Clinical Bioinformatics
Required skills
Ph.D. in bioinformatics, computational biology, genomics or a related discipline, 2 years of industry experience post Ph.D., proficiency with large-scale bioinformatics analyses, strong scientific acumen and statistical rigor, experience analyzing large-scale single-cell or spatial transcriptomics datasets, 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, Hands-on research experience in cancer or autoimmune diseases, 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
Technologies
10x Genomics single-cell and spatial assay technologies, single-cell or spatial transcriptomics datasets, Linux environment, Snakemake, Nextflow, Martian, HPCs, 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
Seniority
Scientist II
Domain
Clinical Bioinformatics, Single-cell and spatial transcriptomics, Diagnostics
