Level

Roche

Post Doctorate Scientist

AI in this role

pytorchtensorflowjax

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections,  where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

The 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!

 

 

Who we are

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.

How we rate this

Post Doctorate Scientist at Roche rates 97 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

PyTorchTensorFlowJax

Questions you could be asked

  1. What's a project where you used PyTorch hands-on?
  2. Walk me through how you've used TensorFlow in your day-to-day work.
  3. What are the limits of Jax that you've run into, and how did you work around them?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: PyTorch, TensorFlow, and Jax. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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