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nan
North America

Research Intern, Machine Learning

New York, NY, USA
2026-04-10

Role Description

**Research Intern (PhD), Machine Learning** =========================================== Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales — from molecules to organisms — enabling us to predict, understand, and program living systems in ways never before possible. Output Biosciences is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI and biology, and backed by top 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. * You will contribute to the development of novel machine learning approaches for biological data analysis and interpretation * You will design and implement experiments to evaluate and improve AI models using large-scale biological datasets * You will collaborate with our interdisciplinary team to tackle complex challenges in molecular biology and drug discovery * You will present your research findings and contribute to publications in top-tier conferences and journals * You will have the opportunity to work on projects that directly impact the future of medicine and biotechnology **Who We're Looking For** ------------------------- * You are currently pursuing a PhD in Machine Learning, Computer Science, Computational Biology, or a related field * You have a strong background in deep learning, with experience in frameworks such as PyTorch or TensorFlow * You have a proven track record of research, demonstrated by publications at conferences such as NeurIPS, ICML, ICLR, or relevant computational biology venues * You are proficient in Python and have experience with large-scale data processing and analysis * You have excellent problem-solving skills and the ability to work independently on complex research problems * You are passionate about applying AI to solve real-world challenges in biology and medicine * You have strong communication skills and can effectively present technical concepts to diverse audiences * You thrive in a fast-paced, startup environment and are excited about making a significant impact in a growing field **Bonus Points** ---------------- * Experience with biological data analysis or computational biology projects * Familiarity with generative AI models, such as transformers or diffusion models * Contributions to open-source machine learning or bioinformatics projects **Our Values** -------------- **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. **What We Offer** ----------------- * 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

Research Intern, Machine Learning

nan

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