2025 Summer Intern - Prescient Design / Machine Learning for Drug Discovery

Prescient Design has joined Genentech's Research and Early Development organization (gRED) in order to apply their cutting-edge technology and machine learning approach to our drug discovery efforts. We believe that Prescient Design's platform and expertise, combined with our growing internal computational capabilities, can ultimately help us bring better medicines to patients, faster.

Our Frontier Research team is focused on advancing fundamental machine learning and its application to real-world challenges in drug discovery. Our mission is to uncover ideas and technologies that will make a meaningful impact on healthcare, shaping the future of how treatments are developed. Instead of focusing on incremental improvements, we tackle complex problems that require creative thinking and a broad perspective, working at a level that enables solutions to be applied across multiple areas.

In biology, many exciting research questions cannot yet be addressed with off-the-shelf ML approaches—they demand not only novel solutions but also new ways of framing the questions themselves, often beyond existing ML paradigms. We believe that causal learning and generalization provide the most promising paths to connect these fields and build robust, impactful solutions.

If you’re excited about advancing research at this intersection, join us on an impactful journey of innovation at Prescient.
 

This internship position is located in New York, on-site.  

The Opportunity

You will develop methods inspired by causal ML to deliver robust, generalizable solutions.

You will collaborate closely with our team in Basel, New York, and San Francisco.

You are expected to contribute to and drive publications, and present your results at internal and external scientific conferences.

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) 

Required Education: You meet one of the following criteria:

Or alternatively have pursued your Master's degree not longer than 12 months prior to the start date. 

Must be pursuing a Ph.D.

Required Majors: Computer Science, Statistics, Applied Mathematics, Computational Biology, Physics, related technical field, or equivalent practical experience. 

Required Skills

Good knowledge of machine learning fundamentals. Familiarity with causal representation learning and/or out-of-distribution generalization would be helpful.

Proven publication record and experience contributing to research communities, including relevant journals or conferences like NeurIPS, ICML, ICLR, AISTATS, UAI, CVPR, ACL, etc.

Detailed hands-on experience on building and training neural networks.

Experience with at least one DL framework (preferably Pytorch), keen to build unconventional models, a knack for getting things to work.    

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.

Experience with ML on biological data is desired.

Relocation benefits are not available for this job posting. 

The expected salary range for this position based on the primary location of New York is $50.00 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.

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