Bioinformatician

Vivodyne creates human data before clinical trials.

We accelerate the successful discovery, design, and development of human therapeutics by testing on large, lab-grown human organ tissues at massive scale, driving technological advancement at the convergence of novel biology, robotics, and AI. We identify and validate new therapeutic targets and de-risk new therapeutic assets by producing clinically translatable multi-omic data from our proprietary, physiologically-realistic human organ tissues at unprecedented scale, speed, and quality. This enables us to produce more human data than all clinical trials in the U.S. combined. We’re financially backed by some of the most selective and successful venture funds, and we have already partnered with a majority of the top 10 multinational pharmaceutical companies to discover and develop better, safer drugs and dramatically reduce the burden of animal testing.

www.vivodyne.com

Role

The Software & Data Science team at Vivodyne tackles some of the hardest problems at the intersection of human biology, large-scale data, and machine learning using uniquely rich imaging and multi-omics datasets from lab-grown human tissues.

We are expanding our capabilities to generate high-throughput -omics data across automated human tissue models, with a primary focus on single-cell and bulk transcriptomics, secretomics, and proteomics. We're looking for a Bioinformatician who can develop new analytical methods and build robust infrastructure to support them at scale.

You will define how we process, store, integrate, and interpret biological datasets, making foundational decisions that shape the long-term utility of our data for internal research, AI/ML model development, and external partners. This means owning both the science (what question does this analysis answer, and how defensible is the conclusion?) and the engineering (does this pipeline run reliably at scale, and can someone else extend it?).

This is a high-impact, cross-functional role. You'll sit within the Software & Data Science organization and collaborate daily with experimental biologists, AI/ML researchers, software engineers, and client-facing teams.

This is a full-time, onsite role in San Francisco.

Responsibilities

Develop and Own Analytical Methods

• Design, implement, and critically evaluate computational approaches for scRNA-seq, bulk RNA-seq, secretomics, and proteomics data including QC, normalization, batch correction, dimensionality reduction, clustering, differential expression, trajectory analysis, and multi-dataset integration.