Machine Learning Intern - Small-Molecule Drug Discovery

2w2 weeks ago

Genentech

South San Francisco, US · Internship · $85,000 – $105,000

About this role

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. You will develop and apply novel machine learning methods to molecular design, advancing drug discovery. The team fosters collaborative innovative thinking for creative ML breakthroughs.

This onsite internship in South San Francisco involves developing machine learning methods using internal Genentech small molecule data. You will design, implement, and evaluate models focused on drug discovery challenges. Execute a dedicated research agenda in this area.

Collaborate closely with machine learning scientists, research engineers, computational biologists, chemists, and biologists on drug discovery projects. Work in a stimulating environment at the forefront of ML research. Engage with talented biotechnology professionals daily.

Own challenging business-critical projects during the intensive 12-week full-time paid program. Present research findings verbally and in writing, targeting top-tier ML venues. Receive a location-based stipend to support internship costs.

Requirements

Must be pursuing a PhD (enrolled student) in computer science, chemistry, or a related field
Basic chemistry and 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

Responsibilities

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