Spring is accelerating the discovery of therapies for aging and its related diseases. A tight integration of biology and machine learning is at our core, and we’re building a rare team of scientists and computational folks that work together closely, fighting disease.
Aging is the single greatest risk factor for the most detrimental diseases on Earth — cardiovascular disease, neurodegenerative disease, pulmonary disease, cancer, muscle wasting, and more — and drugs that slow the biological damage accumulated while aging have the potential to reduce the incidences of these diseases, possibly simultaneously. We believe that in the not-too-distant future, the discovery of therapies for aging will provide some of the most effective tools in history for reducing our burden of disease and extending our healthy lifespan.
Our mission is to dramatically accelerate the realization of that future. And we’re bringing a new set of machine learning tools to bear on this challenge.
Yes, you belong
We are building a cross-functional team. We don’t expect you to have a background in machine learning, just as we don’t expect our computational folks to be expert biologists. We do expect our teams to work respectfully and closely, learning together every day.
We value building a diverse, inclusive environment and welcome all applicants regardless of gender, sexual orientation, ethnicity, race, education, age, or other personal characteristics.
- Record of past successes. You have a track record of successful execution of multiple scientific projects.
- Education. PhD (or similar experience) in immunology or a related field.
- Broad proficiency. You’ve shown proficiency in a wide range of in vitro and in vivo research approaches.
- Technical expertise in flow cytometry and immunological assay development. Experience designing and executing cell-based assays to assess immune function with primary cells.
- Knowledge of mouse disease models. Experience designing and applying mouse models to evaluate immunomodulating drug candidates (e.g. models of autoimmunity, infectious disease, vaccination, and/or cancer).
- Familiarity w/ fluorescence microscopy and cell culture.
- Open-minded and collaborative. You’re excited to work closely with experts in a different field (machine learning), learn from each other, and incorporate new approaches into your expertise.
- Tends towards ownership. You do anything necessary to solve the problem at hand.
- Maturity in face of ambiguity. You help define questions instead of just answering them. You work to resolve ambiguity — and you’re comfortable making decisions when it remains.
- Crisp communicator. You excel at crisp, concise written or spoken communication. You love learning and teaching others in a cross-functional team (we’re biologists, computational folks, and more).
- Driven by impact. You’re most motivated when working on a problem of important consequence, no matter what’s necessary to do so.
Nice to have
- 2+ years of industry or post-PhD experience
- High throughput screening experience
- Competitive salary and equity in a growing, well-funded startup
- Excellent medical, dental, and vision coverage
- Generous vacation policy
- Healthy feedback-focused environment — leadership will have high expectations, regularly share constructive feedback, expect you to grow, and welcome receiving feedback from you
A unique moment
We have deep support from some of the best investors in the world: General Catalyst, First Round, Felicis, Laura Deming’s Longevity Fund, pharma/biotech angels, and many more. Our advisors are world leaders in aging research, senior execs at pharma, and top tech entrepreneurs.
And at the same time, we’re just getting started. You’re joining a team that has the funding needed to be ambitious while still early enough to help define our culture, choices, and success. Our expectations of you — and of ourselves — are high.
To fighting disease, together!