Ph.D Position on Machine Learning in Biomechanics (m/w/d)

01.09.2025, Wissenschaftliches Personal

A Ph.D. position is available in our group to contribute to the development of efficient, certifiable, and practical solutions for inverse problems in diagnostic biomechanics, with a particular focus on elastography. The project builds on our recently developed Weak Neural Variational Inference
(WNVI) framework and aims to advance its capabilities in the following directions:
• Scalability: Extending methods to high-dimensional and three-dimensional elastography
problems using neural operator representations.
• Computational efficiency: Designing adaptive and physics-aware strategies (e.g., optimized residual selection, physics-based zooming) for real-time inference.
• Practical usability: Developing robust, user-friendly frameworks for multimodal elastography and enabling deployment on portable devices (e.g., smartphones) for real-time diagnostics.
The research combines continuum mechanics, machine learning, computational mathematics, and probabilistic modeling, with direct applications in medical imaging and beyond.

Details can be found in the link below.

Kontakt: p.s.koutsourelakis@tum.de