Research Intern (PhD), Machine Learning

Job Description

Job Description

Output has built a biological reasoning model that understands biology at the scale and complexity life actually operates. Our model independently learned the principles of molecular interactions, opening up drug treatments that were previously impossible. We're already generating therapies that traditional approaches cannot reach. The hardest problems in both AI and biology are being solved here, and there is room for you to own one.

Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator.

Our internships offer flexible commitment, with a minimum of 20 hours per week, ranging 12 to 24 weeks. We have various start dates available to accommodate your academic schedule. There may be opportunities for full-time employment upon successful completion of your PhD.

The Role

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.

About You

• 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

Bonus Points

• 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

❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions.

Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards.

Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community.

Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner.

Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling.

• We encourage new and different ideas, creativity and contrarian thinking

• Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you

• You own your day-to-day management. What we care about is that we all hit our milestones

• Competitive salary and equity in a growing, well-funded startup

• Excellent medical, dental, and vision coverage