Summer Intern - Machine Learning Drug Discovery, Prescient Design

Position: 2024 Summer Intern - Machine Learning For Drug Discovery, Prescient Design 2024 Summer Intern - Machine Learning for Drug Discovery, Prescient Design 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 drug discovery. Our team fosters a collaborative environment 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, CAon-site.

Key Responsibilities

You will develop machine learning methods for the analysis of molecular data and processes, with a focus on small molecules Collaborate closely 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 Report and present research findings and developments including status and results clearly, verbally, and in writing (publishing in top-tier ML venues) Program Highlights Intensive 12-week, full-time (40 hours per week) paid internship Program start dates in May/June (Summer) Mentorship by a Prescient Design AI Scientist Ownership of challenging and impactful business-critical projects Work with some of the top machine learning for drug discovery researchers in the biotechnology industry Deliver final presentations of project work to senior leaders Professional and personal development curriculum throughout the program, including networking opportunities, workshops, and panel discussions Who You Are (Required) Required education: Must be pursuing a PhD (enrolled student) Required majors: In the physical or life sciences (e.g Chemistry, Biology, Physics), or quantitative field (e.g. Computer Science, Statistics, Mathematics) Required skills: Demonstrated computational research experience, as evidenced by publications, public code repositories, or equivalent Hands-on experience applying machine learning to tackle scientific problems Excellent communication, collaboration, and interpersonal skills Fluent in Python and experience with modern Python frameworks for deep learning (e.g. PyTorch or Tensor Flow)

Preferred Qualifications

Strong research interest in drug optimization and discovery, chemical properties prediction and generative AI for molecular design

Experience

with one or more cheminformatics or drug discovery toolkits (e.g. Open Eye, Schrodinger, RDKit, Open Babel)

Experience

working with large chemical and biological datasets, including graph, sequence, and structure-based data Complements our culture and the standards that guide our daily behavior & decisions: Integrity, Courage, and Passion. Relocation benefits are not available for this job posting. The expected salary range for this position based on the primary location for this position in 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, and we embrace the increasingly diverse world around us.

Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status. #J-18808-Ljbffr