Research Assistant UE fixed term 01.10.2026-30.09.2027 100%

Quality through innovation.

Your challenge

Develop and maintain software tools for the annotation and automated extraction of clinically relevant parameters from orthopaedic radiographs across different joints and clinical populations.
Design and implement user-friendly annotation interfaces to facilitate efficient expert annotation by orthopaedic surgeons.
Develop, train, and validate state-of-the-art machine learning models for automated radiographic image analysis.
Curate, process, and manage large anonymized medical imaging datasets for AI development and validation.
Evaluate algorithm performance, optimize model accuracy, and contribute to software testing and quality assurance.
Contribute to scientific publications, conference presentations, and collaborative research projects.
Serve as the group's reference for software engineering and machine learning methods, including training and support.

Bachelor's or Master's degree in Data Science, Computer Science, Artificial Intelligence, or a related field.
Strong programming skills in Python.
Experience with machine learning, computer vision, and deep learning frameworks (e.g. PyTorch or TensorFlow).
Experience with software development and version control (Git).
Interest in translational AI research and medical imaging; experience with medical image analysis is an advantage.
Good English communication skills; German is an advantage.
Curious, proactive, and self-motivated, with the ability to independently develop and evaluate software and machine learning solutions under scientific and clinical guidance.