Pioneering Intelligence: Data Science Co-Op (Embedded Science Team)

Pioneering Intelligence is a product of Flagship Pioneering's venture creation engine that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the company’s Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

Welcome to Flagship Pioneering Co-Op Program for the cohort dreaming big and taking courageous leaps. You'll join fellow peers across our ecosystem of companies and learning firsthand how we build first-in-category companies. You’ll have access to enrichment sessions, a dedicated professional development track, and a mentor that help guide you toward your next step. By the end, you will carry on a meaningful project outcome, a genuine network, and a front-row view of how Flagship pioneer new ventures that change the world.

Our Co-ops will work on challenging problems in machine learning and computational science for the life-sciences. They will work closely with a team of interdisciplinary scientists consisting of ML and domain experts to advance the state-of-the art in machine learning and contribute to our ongoing efforts. This is an exciting opportunity to be part of a fast-paced, highly dynamic entrepreneurial environment. We work on problems and use techniques like:

• Generative models for biomolecular design including flow matching, diffusion, and language models.
• Self-learning agentic systems.
• Biophysical simulation.

• →Work with an interdisciplinary team of scientists to build models, organize data and deliver computational solutions.
• →Experiment with diverse datasets and novel techniques. 
• →Communicate your work to a multi-disciplinary audience.

• Fluency in Python and experience implementing ML methods with standard tools and packages (e.g., PyTorch, JAX).
• Readiness to deep dive into the biology/physics/chemistry of the platform companies we build

• Publications or experience in CS, ML, Computational Chemistry/Biology or a similar computational field.
• Experience with generative models, natural language processing, graphical neural networks, reinforcement learning, or similar.
• Familiarity with software development, including git and public cloud computing resources (e.g. AWS, GCP, Azure).