Computational Drug Discovery Intern (2026)

COMPANY

Octant is pioneering a new generation of precision medicines by combining synthetic biology, chemistry, and AI/ML to tackle complex cellular mechanisms driving human disease. We are a small molecule therapeutics company scaling drug discovery to unlock therapies for genetically defined and historically intractable diseases.

JOB DESCRIPTION

We're looking for a computational drug discovery intern to join Octant this summer in a program funded by the Gates Foundation to identify small-molecule drugs targeting HPV-driven cancers. In this role, you'll work alongside our computational and experimental teams to build and iterate on machine learning models, explore molecular representations and structure-activity relationships, and help drive compound design and prioritization from data to decision.

THIS INTERNSHIP MIGHT BE GREAT FOR YOU IF YOU ARE/HAVE:

• Currently enrolled in or recently completed a BS or MS in a quantitative field (CS, bioinformatics, applied math, data science, computational biology, or adjacent)
• Proficient in Python for data analysis and scripting (pandas, numpy, scikit-learn at minimum)
• Experience building or training ML models on real datasets, not just coursework exercises
• At least one substantive research experience (academic lab, industry internship, or independent project) where you drove a project from question to result
• Familiarity with version control (git) and working in shared codebases
• Coursework or research exposure in at least one biological science area
• Ability to communicate results to both computational and experimental audiences
• Comfort with ambiguity and fast iteration. The project work is on a weekly cadence, which means making judgment calls with incomplete data, not waiting for perfect information

EVEN BETTER IF YOU HAVE:

• Hands-on experience with molecular representations (SMILES, fingerprints) or cheminformatics toolkits (RDKit, DeepChem)
• Experience with cloud/distributed compute environments (Databricks, Spark, or similar)
• Understanding of structure-activity relationships, compound libraries, or hit expansion concepts
• Demonstrated ability to work across the computational-experimental boundary (e.g., designed an analysis that informed a wet-lab decision, or interpreted assay data to guide a model)
• Familiarity with active learning or Bayesian optimization frameworks
• Experience building or working with agentic systems, LLM tool-use pipelines, or multi-step automated workflows
• Familiarity with prompt engineering and structured output parsing from language models
• Experience with workflow orchestration or pipeline tools (Databricks, Airflow, or similar)
• Comfort designing and consuming APIs or integrating across multiple tools/platforms programmatically
• Experience with software engineering best practices beyond scripting (testing, error handling, logging, modular code design)
• Familiarity with database interactions (SQL, querying structured data stores) in a production or semi-production context

Optional: Along with your application, please share a paper/preprint/software repo that best highlights your strengths so we can better understand the work you've led. If there is nothing public, please summarize that work in a few paragraphs. 

The pay range for this role is $1,400 to $1,500 per week, depending on experience. The duration of the internship is up to 10 weeks.

Octant is located in Emeryville, California and we work onsite.

Octant is an equal opportunity company that values applicants of all backgrounds. We’re committed to fostering an inclusive and supportive work environment. We value less traditional backgrounds, and may consider an equivalent combination of knowledge, skills, education, and experience to meet minimum qualifications. We know that confidence-gap and imposter syndrome can get in the way of meeting spectacular candidates, so please don’t hesitate to apply — we’d love to hear from you.