Application Guide

How to Apply for AI Research Scientist Intern (Summer 2026)

at Flagship Pioneering

🏢 About Flagship Pioneering

Flagship Pioneering is unique as a bioplatform innovation company that doesn't just invest in startups but actively invents and builds platform companies from scratch, focusing on transformative human health and sustainability solutions. With over 100 scientific ventures originated, it offers the rare opportunity to work at the earliest stages of breakthrough scientific discovery, bridging fundamental research with real-world impact through its venture creation model.

About This Role

This AI Research Scientist Intern role involves conducting cutting-edge research at the intersection of machine learning and biology, working with interdisciplinary teams to advance state-of-the-art techniques on large biological datasets. You'll tackle fundamental problems in ML for biology/chemistry, potentially including generative models, mechanistic interpretability, or agentic systems, with the potential to contribute to Flagship's venture creation pipeline and publish impactful research.

💡 A Day in the Life

A typical day might involve collaborating with biologists to understand a new dataset or biological problem, implementing and experimenting with ML models in Python/PyTorch on large-scale biological data, and participating in interdisciplinary team meetings to discuss research progress. You'd likely spend time reading recent ML papers relevant to your biological focus areas and preparing research presentations for both technical and non-technical audiences within Flagship's ecosystem.

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🎯 Who Flagship Pioneering Is Looking For

  • Current PhD student with demonstrated ML research experience specifically applied to biological or chemical problems (not just general ML)
  • Hands-on experience implementing ML methods in Python with PyTorch/JAX and working with large biological datasets
  • Strong interdisciplinary communication skills to collaborate with biologists/chemists and present research to diverse audiences
  • Research mindset aligned with Flagship's platform approach - thinking about scalable solutions rather than single applications

📝 Tips for Applying to Flagship Pioneering

1

Highlight specific ML applications to biology/chemistry in your resume - mention datasets used, biological questions addressed, and ML techniques applied

2

Tailor your research statement to Flagship's platform mentality: discuss how your work could scale across multiple biological problems or ventures

3

Reference specific Flagship ventures (like Generate Biomedicines, Tessera Therapeutics, etc.) and how your skills could contribute to their platform technologies

4

Demonstrate your ability to communicate across disciplines by describing past collaborations with biologists/chemists in your application materials

5

If you have publications, emphasize those in computational biology/chemistry venues (not just general ML conferences) to show domain relevance

✉️ What to Emphasize in Your Cover Letter

['Your specific experience applying ML to biological/chemical problems and the tangible outcomes', "How your research interests align with Flagship's focus areas (generative models for biology, interpretability, agentic systems for scientific discovery)", 'Your ability to work in interdisciplinary teams and communicate complex ML concepts to non-technical scientists', "Why Flagship's venture creation model appeals to you over traditional academic or industry research roles"]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Study Flagship's portfolio companies (especially those using ML/AI like Generate Biomedicines, Cellarity, etc.) and their platform technologies
  • → Understand Flagship's venture creation process - how they go from scientific concept to platform company
  • → Research Flagship's leadership and their scientific backgrounds to understand the company's technical culture
  • → Review recent publications or talks from Flagship scientists to understand current research directions at the ML-biology intersection

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Deep dive into your ML research applied to biology/chemistry - expect technical questions about your methods and biological insights gained
2 How you would approach a novel biological problem using ML, emphasizing platform thinking rather than single-solution approaches
3 Technical questions about implementing specific ML techniques (generative models, interpretability methods) for biological data
4 Your experience collaborating with domain scientists and communicating research findings across disciplines
5 Questions about Flagship's venture creation model and how you see ML research contributing to platform company development
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⚠️ Common Mistakes to Avoid

  • Presenting generic ML experience without clear connections to biological/chemical applications
  • Focusing only on technical ML skills without demonstrating ability to collaborate with domain scientists
  • Showing interest only in academic research without understanding/appreciation for Flagship's venture creation model

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Flagship Pioneering!

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