Tech Stack

Description

You will implement rigorous computational and statistical methods for single-cell and spatial transcriptomics data analysis, deriving clinically meaningful insights from large-scale biomedical datasets to power next-generation clinical diagnostics.

Requirements

• Ph.D. in bioinformatics, computational biology, genomics or related discipline
• Minimum 5 years of industry experience post Ph.D.
• Experience analyzing large-scale single-cell or spatial transcriptomics datasets
• In-depth understanding of statistical methods assumptions, limitations and caveats
• Experience developing and optimizing high-performance, scalable code
• Proficiency working in a Linux environment
• Goal-oriented, self-motivated and independent problem solver
• Meticulous attention to detail and conscientious work ethic

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