Computational Drug Discovery Intern
3w3 weeks agoOctant
Emeryville, US · Internship · $70,000 – $75,000
About this role
Octant pioneers a new generation of precision medicines by combining synthetic biology, chemistry, and AI/ML to tackle complex cellular mechanisms driving human disease. This internship joins a Gates Foundation-funded program to identify small-molecule drugs targeting HPV-driven cancers. Work alongside computational and experimental teams to advance drug discovery.
Build and iterate on machine learning models using real datasets. Explore molecular representations and structure-activity relationships. Help drive compound design and prioritization from data to decision in a fast-paced environment.
Collaborate in a small molecule therapeutics company scaling drug discovery for genetically defined diseases. Operate on a weekly cadence with comfort in ambiguity and incomplete data. Communicate results to both computational and experimental audiences.
Gain hands-on experience in a substantive research project from question to result. Share a paper, preprint, or software repo highlighting strengths with application. Participate up to 10 weeks onsite in Emeryville.
Requirements
- 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 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 on weekly project cadence
Responsibilities
- Build and iterate on machine learning models
- Explore molecular representations and structure-activity relationships
- Drive compound design and prioritization from data to decision
- Work alongside computational and experimental teams
- Analyze real datasets for model training and validation
- Make judgment calls with incomplete data on weekly cadence
- Integrate insights from experimental assays into computational workflows
Benefits
- $1,400 to $1,500 per week depending on experience
- Up to 10 weeks duration
- Equal opportunity employer committed to inclusive work environment
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