2026 Summer Intern - Machine Learning for Small-Molecule Drug Discovery

2026 Summer Intern - Machine Learning for Small-Molecule Drug Discovery

Department Summary

We seek a highly motivated research intern to join the Small-Molecule Machine Learning for Drug Discovery Team at Prescient Design, within Genentech Research and Early Development (gRED). As a successful candidate, you will develop and apply novel machine learning methods to molecular design with the ultimate goal of advancing drug discovery. Our team fosters a collaborative approach that stimulates innovative thinking and the potential for creative breakthroughs at the forefront of ML research.

This internship position is located in South San Francisco, on site.

The Opportunity

• Develop and apply machine learning methods that learn from internal Genentech small molecule data.

• Collaborate closely on machine learning projects for drug discovery with machine learning scientists, research engineers, computational biologists, chemists, and biologists.

• Develop and execute a research agenda focused on machine learning for drug discovery.

• Design, implement, and evaluate machine learning models.

• Clearly report and present research developments and findings, both verbally and in writing (publishing in top-tier ML venues).

Program Highlights

• Intensive 12-weeks, full-time (40 hours per week) paid internship.

• Program start dates are in May/June (Summer)

• A stipend, based on location, will be provided to help alleviate costs associated with the internship.

• Ownership of challenging and impactful business-critical projects.

• Work with some of the most talented people in the biotechnology industry.

Who You Are

Required Education
You meet one of the following criteria:

• Must be pursuing a PhD (enrolled student).

Requires Majors: Computer science, chemistry, or a related field.

Required Skills:

• Basic chemistry & cheminformatics knowledge.

• Machine learning expertise.

• Fluent in Python and experience with modern Python deep learning frameworks.

• Interest in drug discovery, chemical property prediction, and applying methods from machine learning academia to real-world problems.

Preferred Knowledge, Skills, and Qualifications

• Excellent communication, collaboration, and interpersonal skills.

• Complements our culture and the standards that guide our daily behavior & decisions: Integrity, Courage, and Passion.

• Strong research interest in drug optimization and discovery, chemical properties prediction.

• Demonstrated computational research experience, as evidenced by publications, public code repositories, or equivalent.

• Experience with one or more cheminformatics or drug discovery toolkits (e.g. OpenEye, Schrodinger, RDKit, OpenBabel).

• Experience working with large chemical and biological datasets, including graph, sequence, and structure-based data.

Relocation benefits are not available for this job posting.

The expected salary for this position based on the primary location of California is $50.00 per hour. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. This position also qualifies for paid holiday time off benefits.

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.