EntryFull TimeInternshipEN
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2026 Summer/Fall Intern - Prescient Design / Machine Learning for Drug Discovery
Department Summary
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 Basel, Switzerland, 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 6 months, full time (40 hours per week) internship
Program start dates are in May/June (Summer)
Ownership of challenging and impactful business-critical projects.
Work with some of the most talented people in the biotechnology industry.
Who You Are (Required)
- Must be pursuing a Ph.D. in Computer Science, Statistics, Applied Mathematics, Computational Biology, Physics, related technical field, or equivalent practical experience. In cases of outstanding excellence, we will also consider applications of master students.
- Good knowledge of machine learning fundamentals. Familiarity with causal representation learning and/or reinforcement learning would be helpful. Experience with ML on biological data is desired, but not necessary.
- 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.
Required Majors:
- You are an enrolled university student in your Master's or PhD programme, or alternatively have pursued your Master's degree not longer than 12 months prior to the start date.
Due to regulations, non-EU/EFTA citizens must provide a certificate from the university stating that an internship is mandatory as part of the application documents, and must be continuously enrolled in their university program for the whole duration of this internship.
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.
A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.
Let’s build a healthier future, together.
Roche is an Equal Opportunity Employer.
