Scientist, Genomics

Retro•Redwood City, CA

1d•$130,000 - $170,000

About The Position

Retro develops therapies for diseases driven by the biology of aging. We focus on cellular reprogramming and autophagy to rejuvenate cell and tissue function with the ultimate aim of adding 10 years to healthy human lifespan. We're building a mission-driven team of accomplished and kind individuals who embrace our startup culture of rapid iteration, transparency, and versatility. We are hiring a high-agency scientist to build genomics platforms that drive the discovery of therapies that rejuvenate cells and tissues. You'll own sequencing workflows end-to-end, working closely with automation and computational scientists to scale what you build and generate the data that enables our frontier models. About you: You want to drive the experimental direction for a research program, not wait to be handed a plan. You're happiest at the bench, building assays, troubleshooting failures, and generating data. You don't just run protocols; you take them apart and make them work for new contexts. You're excited to collaborate with computational scientists and automation engineers, but your core identity is as an experimentalist. You want to work on something ambitious enough that it might not work, and you can't think of anything more worth trying than extending healthy human lifespan.

Requirements

Have a Ph.D. in Biology, Genomics, or a related discipline (anyone with an exceptional track record of building genomics technologies welcome).
Have deep experience with NGS library prep, sequencing, and QC.
Have experience with cell culture and molecular characterization techniques.
Have worked with single-cell technologies (10x Genomics or similar).
Have experience with epigenomics assays (ATAC-seq, CUT&Tag, or methylation profiling).
Have worked with reprogramming or differentiation systems.
Have a track record of adapting protocols from literature and making them work in new contexts.
Are a generalist who learns quickly and enjoys working across different problem types.
Are comfortable with ambiguity, move fast, and can drive projects forward independently.

Nice To Haves

Have developed novel assays or measurement technologies.
Have worked with high-throughput screening or transferred manual protocols to automated platforms.
Have computational skills (Python, R) for basic data QC and visualization.
Have a history of working with cross-disciplinary teams (computational, automation, engineering).

Responsibilities

Design, execute, and optimize diverse genomics experiments (RNA-seq, ATAC-seq, single-cell assays), owning the full process from sample preparation through library construction, sequencing, and QC.
Build custom genomics platforms that give us the readouts we need when off-the-shelf methods fall short.
Culture and treat cells for screening campaigns, running functional assays alongside genomic readouts to validate hits.
Partner with automation engineers to transfer genomics protocols to automated platforms, enabling systematic discovery at scale.
Collaborate with computational scientists to generate the data that trains predictive models and guides the next round of experiments.