Impact 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 biology, just as we don't expect our biologists to be experts in ML. 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.
Lead computational research into questions which stem from understanding biology through terabytes of high resolution imaging data.
Develop new machine learning models and methods to learn the biology of aging present in microscopy and histology data.
Pioneer methods to deconvolute real biological signal from confounding effects.
Work closely with cell and aging biologists to push the iteration of various hypotheses in both the wet and dry lab.
Generate and prioritize new computational research questions into modeling biological changes through images.
Overcome analytical challenges inherent in the study of high throughput biological data.
You're most motivated when working on a problem of important consequence, no matter what's necessary to do so.
PhD or equivalent experience in a relevant, quantitative field such as computer science, physics, statistics, applied math, electrical engineering, etc.
Demonstrated experience applying and advancing the latest techniques in computer vision on challenging datasets.
Extensive experience developing models for diverse machine learning tasks such as segmentation, recognition, classification, domain adaptation, etc.
Ability to efficiently clean and process raw datasets into a format suitable for machine learning.
Strong engineering skills, including thorough experience with Python data packages, classical machine learning libraries, and deep learning frameworks.
Excellent communication and teamwork skills to take advantage of our highly collaborative environment, working with both computational and experimental scientists.
A passion for innovation and demonstrated initiative in tackling new areas of research
Nice to have
Strong publication record related to applying computer vision methods to biological imaging data.
Extensive hands on experience working with microscopy data or similar biomedical / biophysical imaging datasets.
Experience working with microscopy data acquisition in various image file formats.
Understanding of the core tenants of cellular biology and molecular processes.
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!