Ph.D. Position in AI for Precision Oncology

The Krauthammer lab (at the University of Zurich) and the Wicki Lab (at the University Hospital of Zurich) are seeking a motivated PhD candidate to work on AI-driven research at the intersection of precision oncology and data science, with a particular focus on leveraging multi-modal clinical data to support personalized cancer treatment decisions.

Your Responsibilities

The primary goal of this position is to develop state-of-the-art machine learning approaches to enhance personalised decision-making in oncology care in the following aspects:

• Developing predictive models to forecast treatment outcomes and side effects based on retrospective observational clinical data.
• Implementing counterfactual inference and causal machine learning methods to identify optimal treatments and evaluate treatment biases.
• Incorporating explainable AI tools (e.g., SHAP values) and uncertainty quantification techniques (e.g., conformal prediction) to enhance the interpretability and reliability of predictions.
• Collaborating closely with oncologists and data scientists to align AI tools with clinical workflows and real-world needs.

You also have the possibilities to expand the research scope to other innovative projects in AI for healthcare and clinical data science.

Your Profile

Minimum qualifications:

• Master’s degree (MSc) in computer science, machine learning, statistics, applied mathematics, or a related discipline.
• Proficiency in Python and core scientific computing libraries (e.g., NumPy, SciPy, Scikit-learn, pandas).
• Experience with at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX).
• Strong foundational knowledge of machine learning and predictive modeling techniques.

Preferred qualifications:

• Knowledge of longitudinal data analysis, time-series modeling, or causal inference methods.
• Experience with explainable AI techniques for model interpretability.
• Familiarity with multi-modal data integration (e.g., clinical, genetic, proteomics).
• Proficiency in Linux systems, Docker, and high-performance computing (HPC) environments.

What We Offer

• Access to state-of-the-art computational resources, clinical datasets, and expert medical collaborators.
• An opportunity to work on cutting-edge AI projects with real-world impact in healthcare.
• A stimulating, interdisciplinary research environment within the University of Zurich and the University Hospital of Zurich.
• Competitive salary and support for attending conferences and publishing in top-tier journals.
• Outstanding working conditions in the vibrant city of Zurich, Switzerland.

Place of Work

Zurich, Switzerland

Start of Employment

Employment start date is flexible and will be mutually agreed upon.

Further Information

For inquiries of this position, please contact bowen.fan@uzh.ch (no application)

How to Apply

Send your application including the following documents to claudia.stenger-gysling@uzh.ch:

• A cover letter detailing your motivation and fit for this position.
• A detailed CV.
• Academic transcripts.
• Contact details for three references.