Single Cell Computational Biologist

South San Francisco
Computational Biology /
About Vevo Therapeutics
We are a biotechnology company based in San Francisco. We are using our in vivo drug discovery platform and  AI models trained on its data to uncover better drugs for more patients. Our Mosaic platform is the first to make in vivo data generation scalable, with single-cell precision, to capture in vivo context of disease at the first step of drug discovery and to better represent patient diversity in drug response over current in vitro assays. We are using Mosaic to build the world’s largest in vivo atlas of how drugs interact with patient cells and how they alter gene function in diverse biological contexts. We are using the unprecedented scale and sophistication of the data in this atlas to train single-cell foundation models that learn context dependency of gene function and help us find novel targets and drugs that are more likely to work in patients.

Your role
The person in this role will lead the analysis of scRNA-seq generated by the Vevo platform, with an emphasis on methodology. Key responsibilities include processing sequencing reads, demultiplexing and cell identity reconstruction, quality control and exploratory analysis, as well as more downstream analysis supporting data integration and hypothesis formulation. This role will involve close collaboration with other members of the computational team who specialize in software engineering, machine learning and data interpretation for therapeutic program formulation.

Qualifications - Required

    • PhD in computational biology or related discipline
    • At least 2 years postgraduate experience (academia or industry) 
    • In-depth experience with single-cell RNA-seq data analysis
    • Familiarity with common bioinformatics, biostatistics and data analysis practices and tools
    • Solid foundation knowledge of mathematics, statistics, computer science and machine learning
    • Solid knowledge of Python and cloud computing environments
    • Ability to work efficiently with large-scale data

Qualifications - Desirable

    • Experience with drug screening data
    • Experience with cancer genomics
    • Practical experience with training deep neural networks

Key Responsibilities

    • Ensure the main bioinformatics pipeline, going from sequencing reads to gene expression and other processed data, reflects state-of-the-art methodology
    • Review and adopt state-of-the-art methodology for batch correction, dimensionality reduction, data integration and more advanced modeling techniques
    • Collaborate closely with other scientists who utilize the platform results to generate hypotheses
    • Collaborate closely with the ML team on foundation models for single cell data


    • Unlimited Paid Time Off (PTO).
    • Monthly Lunch budget
    • One-time Office set up budget
    • US Employees: HMO Kaiser Platinum and PPO Anthem Gold medical as well as vision and dental plans for both the employee and dependents.
    • Canadian Employees: Manulife Silver including medical, vision and dental.
$120,000 - $250,000 a year
This hybrid role does not necessitate daily on-site attendance, but it does require the ability to access our offices in either South San Francisco, CA, or Toronto, ON; we welcome applications from candidates in these regions or those willing to relocate to the Bay Area or the Greater Toronto Area. Please note, we have one role open to two geographical locations.