Sustainable Development GoalsSDG 3. GOOD HEALTH & WELL BEING
At Recursion, our mission is to decode biology to radically improve lives. This mission includes building the most scalable drug discovery platform in the history of the BioPharma industry with a combination of biological and laboratory expertise, automation engineering, and cutting-edge computational tools. To this end, we have generated and continue to grow one of the largest biological datasets in existence in our labs—images of billions of cells under millions of biological and chemical perturbations.
With treatments for hundreds of diseases in our sights, we’ve built a data science team with domain expertise in computer science, physics, biology, mathematics, applied statistics, and more. Together, we develop the tools and methods to turn our experimental data into treatments for pathologies that affect the lives of countless individuals. If you think you can make a difference in this goal, please, join us and we will save lives together.
The Impact You’ll Make
You will work closely with Biologists, Chemists, Engineers, and Automation Scientists to develop scalable solutions that impact our drug-discovery pipeline
- Develop novel analyses leveraging the world’s largest single-source dataset of human cellular images to build a map of biology.
- Design scalable analysis tools that will be integrated into the Recursion platform. These tools will allow rapid improvements to our inference-based drug-discovery platform.
- Create and Evaluate inference strategies to discover therapeutics using Recursion’s map of human cellular biology.
- Develop visualization tools to aid biologists in the interpretation of phenotypic relationships observed in our internally derived data.
The Team You’ll Join
You will be joining a fast-growing cross-functional data science team at Recursion that tightly collaborates with ML scientists, engineers, biologists, and chemists. The main objective of the team is to develop inference capabilities of the Recursion platform.
The Experience You’ll Need
- A firm grasp of the fundamentals of probability, statistics, and machine learning.
- High fluency with the Python data stack (numpy, pandas, sklearn, etc).
- Experience working with distributed version control systems such as git and experience with peer code review.
- A track record of outstanding past projects, publications, or presentations.
- Preferred: Background analyzing biological datasets
Professional: 2+ years in industry setting on a data science team, or PhD in computational science applying ML methods to large data sets, or equivalent experience in the application of ML and analytical tools in postdoctoral work.
Senior: 2+ years postdoctoral experience in industry or academia on directly relevant subjects, and/or experience as a technical lead driving execution in these areas.
The Benefits/Perks You’ll Enjoy
- 100% Coverage of health, vision, and dental insurance premiums
- 401(k) with generous matching (immediate vesting)
- Stock option grants
- Two one-week paid company closures (summer and winter)
- Flexible vacation/sick leave
- Generous paid parental leave (including adoptive)
- Onsite daycare facility*
- Commuter benefit and vehicle parking to ease your commute*
- Complimentary chef-prepared lunches and well-stocked snack bars*
- Monthly fitness/wellness stipend
- One-of-a-kind 100,000 square foot headquarters complete with a 70-foot climbing wall, showers, lockers, and bike parking*
*Subject to change for remote-based employees during the COVID-19 pandemic
More About Us
Recursion’s mission is to decode biology to radically improve lives. Unraveling the exceptional complexity of biological systems and delivering the next generation of biotherapeutics at unprecedented speed and scale can only be achieved by bridging life science and technology. Recursion is the leader in digital biology, and has built the world’s most advanced ultra-high throughput wet-lab and machine learning platform. Recursion’s ability to generate proprietary, high-dimensional, multi-modal and relatable datasets of human cellular biology at massive scale, and apply advanced machine learning approaches to reveal novel biological relationships, has resulted in a proven, target-agnostic drug-discovery engine.