Fall 2026

Research Intern

Machine Learning

Posted on 7/4/2026

Output Biosciences

Output Biosciences

1-10 employees

AI-driven preventative therapeutics for chronic disease

No salary listed

San Francisco, CA, USA + 1 more

More locations: New York, NY, USA

In Person

Category
AI & Machine Learning (1)
Required Skills
Python
Pytorch
Machine Learning
Requirements
  • You are currently pursuing a PhD in machine learning, computer science, computational biology, physics, mathematics, or a related field
  • You have a strong research track record, demonstrated by publications or submitted work at venues such as NeurIPS, ICML, ICLR, or relevant computational biology conferences
  • You have hands-on experience designing and running ML experiments, including training models and analyzing results
  • You are proficient in Python and PyTorch, and comfortable working with large-scale datasets and GPU infrastructure
  • You can work independently on a research problem: scoping an approach, running experiments, interpreting results, and communicating findings clearly
Responsibilities
  • You will own a research project that directly advances Output's research and its path to new therapies. This is not a side project: your work will contribute to the same models and methods the full-time team builds on.
  • We will select a project together based on your research interests and our priorities, with a path to publishing your work at top-tier venues and the opportunity to continue with additional projects throughout the year.
  • The internship offers a minimum of 20 hours per week, for 12 to 24 weeks, with various start dates available to accommodate your academic schedule.
  • There may be opportunities for full-time employment upon successful completion of your PhD.
Desired Qualifications
  • You have experience applying machine learning to biological, chemical, or molecular data
  • You have a background in computational biology, biophysics, chemistry, or a related natural science
  • You have experience with generative models, representation learning, or self-supervised learning
  • You have contributed to open-source machine learning or computational biology projects

Output Biosciences develops preventative therapeutics to extend human healthspan by combatting chronic diseases. It uses computational biology and AI to discover therapies that can prevent diseases faster, with safer profiles and easier manufacturing, enabling quicker development timelines. The company differentiates itself by integrating biotech expertise with AI to create therapies focused on prevention, and by forming partnerships with pharmaceutical companies, licensing its technologies, and pursuing direct therapy sales. Its goal is to bring preventive treatments to market within months, shifting drug development toward stopping chronic diseases before they start.

Company Size

1-10

Company Stage

Seed

Total Funding

$130K

Headquarters

New York City, New York

Founded

2020

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Simplify's Take

What believers are saying

  • Large Biological Models could accelerate chronic disease prevention across diabetes, heart disease, arthritis.
  • AI-driven drug discovery platform attracts pharma partnerships and licensing revenue opportunities.
  • Team expansion signals commitment to scaling biological reasoning model development and commercialization.

What critics are saying

  • Only $500K raised since 2021 insufficient for capital-intensive biotech model training and trials.
  • Six-person team cannot compete against Recursion, Insitro, Exscientia with 100+ PhDs and billions.
  • FDA's March 2026 AI/ML validation guidelines block IND filings without rigorous preclinical data.

What makes Output Biosciences unique

  • Biologically-aware generative AI architecture designed for nonlinear, high-dimensional biological data.
  • Preventative therapeutics focus enables faster discovery and manufacturing versus traditional drug development.
  • Y Combinator-backed team includes repeat founders, physicians, and computational systems biology researchers.

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