PhD Position - Machine Learning in Ocular Biomechanics 100 %
Universität Bern
Bern
Key information
- Publication date:20 January 2026
- Workload:100%
- Place of work:Bern
Job summary
Join the ARTORG Center at the University of Bern, a hub for biomedical innovation. Collaborate in a dynamic environment focused on AI tools for refractive surgery.
Tasks
- Develop patient-specific biomechanical models using machine learning.
- Analyze how corneal biomechanics affect visual outcomes.
- Design tools to optimize surgical treatment strategies effectively.
Skills
- Master's in computer science, engineering, or applied mathematics required.
- Strong experience in machine learning and computer vision essential.
- Solid Python programming skills for effective model development.
Is this helpful?
The ARTORG Center for Biomedical Engineering Research is a multidisciplinary research center at the University of Bern developing medical technology solutions from basic research to clinical applications.
Every year, millions of people undergo refractive surgery to correct their vision, yet outcomes remain unpredictable for patients with complex corneal conditions. Join us in developing AI-powered tools that could revolutionize how we plan and predict surgical outcomes for patients with severe visual impairment.
About the project
The Computational Bioengineering Group invites applications for a 3-4 year PhD position in machine learning and ocular biomechanics. You will develop patient-specific biomechanical models of the cornea integrated with machine learning to understand how corneal biomechanics influence visual outcomes and support prediction, treatment, and planning of refractive interventions for patients with severe visual impairment.
This SNSF-funded project is conducted jointly with the Swiss Federal Institute of Technology Lausanne (EPFL), the University of Basel (unibas), and Bern University Hospital (Inselspital). The candidate will work closely with engineers, clinicians, and data scientists in a strong translational research environment.
Research environment
The Computational Bioengineering Group develops experimental and computational methods in biomechanics to address clinically relevant problems. The group combines finite element modeling, medical image analysis, experimental tissue characterization, and data-driven methods to develop new diagnostic approaches, support surgical planning, and contribute to the design of medical technologies.
Tasks and responsibilities
- Develop medical image analysis tools for patient-specific finite element modeling
- Quantify biomechanical impact of surgical treatments on visual outcomes
- Design machine learning methods to accelerate simulations and predict outcomes
- Identify optimal treatment strategies from preoperative data
Required qualifications
- Master's degree in computer science, engineering, or applied mathematics
- Experience in computer vision and machine learning
- Solid Python programming for machine learning
- Background in mechanics and computational methods
- Finite element analysis experience (strong asset)
- Working in a medical regulatory environment would be a strong advantage
- Strong English communication skills
What we offer
- International environment in a leading biomedical engineering center
- Close clinical interaction with real-world data access
- Multidisciplinary team expertise (biomechanics, ML, clinical research)
- Publication and conference opportunities in high-impact venues
- Competitive SNSF salary with Swiss social benefits
- Free German language courses
Application procedure
Interested candidates should submit the following documents electronically to Prof. Philippe Büchler, E-Mail schreiben
- Curriculum vitae, including contact details of references
- Motivation letter describing research interests and career goals
- Abstract of the Master's thesis
- Academic transcripts
Application deadline: February 15, 2026 | Starting date: May /June 2026
