Applications are invited for a fully funded PhD position in Machine Learning in Medicine at the University of Bern, Switzerland. Supervised by Prof. Dr. Lisa Koch, head of the Machine Learning in Medicine Lab (MLM Lab), the selected candidate will conduct cutting-edge research developing trustworthy AI and multimodal machine learning models to characterize and predict chronic disease progression in collaboration with Inselspital, Bern University Hospital.
Quick Overview
| Designation | PhD Candidate / Doctoral Researcher |
| Host Institution | University of Bern |
| Research Group | Machine Learning in Medicine Lab (MLM Lab) |
| Research Focus | Machine Learning for Healthcare & Multimodal Disease Progression Modelling |
| Location | Bern, Switzerland |
| Funding / Salary | CHF 50,042 gross per annum (including 13th month salary) |
| Application Deadline | Open until filled (Early applications strongly encouraged) |
Designation
PhD Student / Doctoral Researcher in Machine Learning in Medicine
Research Area
The research is positioned at the intersection of computer science, biomedical engineering, and clinical healthcare, with a specific focus on:
- Multimodal representation learning across medical imaging, time series (wearable sensor data), and tabular clinical records.
- Disease progression modelling leveraging cross-sectional and sparse longitudinal data.
- Causal machine learning to distinguish true disease progression from treatment effects.
- Machine learning under real-world constraints: missing modalities, irregularly sampled signals, and label noise.
- Fairness, reliability, and bias mitigation across diverse demographic patient subgroups.
- Trustworthy ML: uncertainty quantification and robustness for clinical deployment.
Location
University of Bern, Bern, Switzerland (with close clinical collaboration at Inselspital, Bern University Hospital).
Eligibility / Qualifications
Interested candidates should meet the following criteria:
- Educational Background: A completed (or near-completion) Master’s degree in a quantitative discipline such as Computer Science, Machine Learning, Data Science, Statistics, Biomedical Engineering, Electrical Engineering, Mathematics, or a closely related field.
- Theoretical Foundation: Solid theoretical grounding in the principles of modern machine learning and statistical data analysis.
- Programming & Technical Skills: Proven practical experience implementing, training, and benchmarking machine learning and deep learning pipelines in Python (e.g., PyTorch, TensorFlow, Scikit-Learn).
- Analytical Mindset: Strong analytical and problem-solving skills, with an inquisitive approach to understanding complex biomedical problems.
- Desirable Asset: Prior experience handling and processing biomedical data (medical imaging, physiological wearable data, or electronic health records) is considered an advantage.
- Language Proficiency: Excellent written and verbal communication skills in English.
Scholarship Description & Benefits
The doctoral candidate will join a collaborative and ambitious team embedded in an expanding medical AI ecosystem in Bern. Key benefits include:
- Remuneration: Competitive annual gross salary of CHF 50,042 (based on standard Swiss university salary scales for 2026 full-time doctoral researchers, including the 13th month salary).
- Supervision & Mentorship: Direct individual guidance and research supervision by Prof. Dr. Lisa Koch in a small, tight-knit group.
- Translational Impact: Direct clinical integration through partnerships with Inselspital, Bern University Hospital, offering immediate clinical context for AI methodologies.
- Research Infrastructure: Access to high-performance computing resources, international collaboration opportunities, and conference travel funding.
- Quality of Life: Bern provides an outstanding standard of living, excellent public infrastructure, and central access to European research hubs.
How to Apply
Candidates must submit their application directly through the University of Bern’s official recruitment portal. A typical complete application includes:
- A comprehensive Curriculum Vitae (CV).
- A cover letter / letter of motivation detailing your research interests, how your profile matches the project goals, and previous relevant project or thesis work.
- Academic transcripts of records and degree certificates (Bachelor’s and Master’s).
- Contact details of at least two academic or professional references.
- A copy of your Master’s thesis or relevant code repository / publication samples (if available).
Last Date for Apply
Applications are reviewed on a rolling basis. The position will remain open until a suitable candidate is selected. Applicants are encouraged to apply as early as possible.
Apply Link
To submit your application or view the official posting, please visit:
Official University of Bern Job Application Portal
