Intern ML for Organoid Engineering

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The Position

The Institute of Human Biology (IHB) is a research center in Basel Switzerland dedicated to engineering advanced human model systems for drug discovery development and precision medicine. The IHB fosters an interdisciplinary environment bridging academic and pharmaceutical research connecting biologists engineers and data scientists. It has close ties to Roches Pharmaceutical Research and Early Development (pRED) organization and Genentech (gRED) and collaborates with leading academic institutions including ETH Zürich University of Basel and EPFL as well as globally. Basel is an international hub for research and innovation cultivating training environments through institutions like the University of Basel and ETH Zürichs Department of Biosystems Sciences and Engineering creating a melting pot of research development and commercialization.

The Opportunity

The ML for Biosystems Engineering group led by Jonas Fleck is seeking a highly motivated intern to develop machine learning methods for organoid phenotyping and high-throughput screening. You will be part of an exciting scientific community at the IHB and receive mentorship by experts in machine learning computational biology and organoid collaboration with computational and experimental scientists you will work with rich high-content datasets and develop and apply state-of-the-art machine learning methods to tackle challenging questions in human biology and disease.

Possible research areas include:

• Predictive ML methods for high-throughput perturbation screens in organoids.

• Multimodal integration methods and foundational models of imaging and genomics data for comprehensive organoid phenotyping.

• Predictive methods for cell fate engineering.

• Methods for causal and mechanism discovery from high-content perturbation experiments.

• Active learning strategies for iterative experimental design (lab-in-the-loop).

Who You Are

To successfully execute the responsibilities of this role candidates must demonstrate the following:

• Masters degree and/or ongoing masters or PhD studies in computational biology computer science machine learning or related technical field

• Proficiency in Python (including familiarity with ML frameworks like JAX/PyTorch) and modern software engineering tools (Git CI/CD and software packaging).

• Excellent communication and data visualization skills with the ability to explain technical concepts and complex findings clearly to non-technical audiences.

• Drive to creatively tackle challenging problems in biomedical research and enthusiasm for translating ML methods to impactful applications in collaboration with experimental scientists.

• Nice-to-have: Experience applying or developing ML methods for biomedical data (genomics imaging scRNA/ATAC-seq) and a matching track record of publications or open-source contributions.

Application Process

• Please upload a current CV and a Motivation Letter where you indicate your preferred start date of the internship.

• Please note that 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 or PhD program for the whole duration of this internship.

Ready to take the next step Wed love to hear from you. Apply now to explore this exciting opportunity!

Who we are

A healthier future drives us to innovate. Together more than 100000 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.

Lets build a healthier future together.

Roche is an Equal Opportunity Employer.