Department of Quantitative Biomedicine
Ph.D. Position in AI for Precision Oncology 100 %
Start of employment will be mutually agreedThe 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.
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.
- 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.
Information on your application
Send your application including the following documents:- A cover letter detailing your motivation and fit for this position.
- A detailed CV.
- Academic transcripts.
- Contact details for three references.
What we offer
Our employees benefit from a wide range of attractive offers. More
What we offer
Further information
Questions about the job
Bowen Fan
Contact Form
Thank you for your message. We will get back to you shortly.
Working at UZH
The University of Zurich, Switzerland's largest university, offers a range of attractive positions in various subject areas and professional fields. With around 10,000 employees and currently 12 professional apprenticeship streams the University offers an inspiring working environment on cutting-edge research and top-class education. Put your talent and skills to work with us. Find out more about UZH as an employer!
More → https://www.uzh.ch/cmsssl/en/explore/work.html
Please apply via our job portal www.jobs.uzh.ch.
The University of Zurich, Switzerland's largest university, offers a range of attractive positions in various subject areas and professional fields. With around 10,000 employees and currently 12 professional apprenticeship streams the University offers an inspiring working environment on cutting-edge research and top-class education. Put your talent and skills to work with us. Find out more about UZH as an employer!
More → https://www.uzh.ch/cmsssl/en/explore/work.html
Please apply via our job portal www.jobs.uzh.ch.
Working at UZH
The University of Zurich, Switzerland's largest university, offers a range of attractive positions in various subject areas and professional fields. With around 10,000 employees and currently 12 professional apprenticeship streams the University offers an inspiring working environment on cutting-edge research and top-class education. Put your talent and skills to work with us. Find out more about UZH as an employer!
More
