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Die Position

The ML for Biosystems Engineering group led by Jonas Fleck at the Institute of Human Biology (IHB) in Basel, Switzerland is seeking a Postdoctoral Researcher to develop machine learning methods for organoid phenotyping and high-throughput screening. Join us to develop next-generation computational methods for drug discovery with complex human model systems.

The Opportunity

You will lead a research project developing computational methods to address important challenges in organoid engineering and drug discovery. Working in a highly collaborative environment with outstanding computational and experimental scientists, you'll develop state-of-the-art statistical and machine learning methods to tackle challenging questions in human biology and disease.

You'll have the chance to work with rich, high-content datasets from complex human model systems, such as large-scale perturbation experiments with multi-modal readouts. In collaboration with experimental scientists at IHB, you will also have the opportunity to shape future experiments, enabling you to develop methods with direct translational impact.

Possible research areas may include:

• Causal inference and mechanism discovery from perturbation experiments
• Predictive modeling and analysis for high-throughput screening
• Computational methods for quantitative comparison of spatial, genomic, and other molecular profiles from organoid models with patient data.

Your work will connect computational innovation with experimental applications, contributing to the development of next-generation human model systems for drug discovery. You will publish your research, contribute open-source tools to the broader scientific community, and gain exposure to drug discovery and development while building your scientific independence as a computational researcher.

Who You are:

• PhD in computational biology, computer science, machine learning, bioinformatics, or related technical fields.
• Track record of conducting impactful independent research, demonstrated through publications, preprints, or substantial research software contributions.
• Strong research experience in statistical or machine learning methods, ideally applied to genomics or other high-dimensional biological data.
• Proficiency in Python and experience with modern ML and scientific computing frameworks such as JAX, PyTorch or TensorFlow.
• Strong scientific programming and software engineering practices, including version control, testing, reproducible research workflows, and agentic development tools.
• Creativity, scientific curiosity, and enthusiasm for developing computational methods that address challenging problems in biomedical research.
• Ability and motivation to work closely with experimental scientists and contribute to collaborative, interdisciplinary projects.

Nice to have:

• Experience applying machine learning to biomedical data, including genomics, imaging, spatial, or multimodal datasets.
• Experience with perturbation experiments, causal inference, high-throughput screening, or predictive modeling.
• Contributions to open-source software or scientific computing tools.
• Experience working closely with experimental collaborators.

Technical details:

• To be considered, your application needs a CV (including a list of relevant publications) and a cover letter describing your research interests.

About the Institute of Human Biology (IHB) & Basel:

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 Roche's 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 Zürich's Department of Biosystems Sciences and Engineering, creating a melting pot of research development and commercialization.

We are looking forward to your application!

Wer wir sind

Eine gesündere Zukunft treibt uns zur Innovation an. Mehr als 100.000 Mitarbeiter weltweit arbeiten gemeinsam daran, wissenschaftliche Fortschritte zu erzielen und sicherzustellen, dass jeder Zugang zur Gesundheitsversorgung hat – heute und für zukünftige Generationen. Durch unser Engagement werden über 26 Millionen Menschen mit unseren Medikamenten behandelt und mehr als 30 Milliarden Tests mit unseren Diagnostik-Produkten durchgeführt. Wir ermutigen uns gegenseitig, neue Möglichkeiten zu erkunden, Kreativität zu fördern und hohe Ziele zu setzen, um lebensverändernde Gesundheitslösungen zu liefern.

Gemeinsam können wir eine gesündere Zukunft gestalten.

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