PhD in Sparse 3D Virtual Histology Imaging (X-ray)

ETH Zürich; Zürich; Vor Ort; CHF 60.000 - 80.000; Vollzeit

Zusammenfassung

ETH Zurich’s X-ray Imaging Professorship seeks a Doctoral Student to advance translational imaging, focusing on machine-learning-based sparse 3D image reconstruction for histopathology of breast tissue biopsies using X-ray phase-contrast radiography and tomography.

You will contribute to data pipelines, algorithm development, and dissemination, while participating in multidisciplinary studies with clinical partners.

Qualifikationen

• Excellent university degree in physics, engineering or computer science.
• Proficiency in computer vision and machine learning with Python.
• Knowledge of X-ray physics and imaging is a plus.
• Strong communication and teamwork skills.

Aufgaben

• Collect grating interferometry X-ray phase-contrast microCT data of breast tissue biopsies.
• Set up data pipelines for synchrotron and lab microCT scans of soft tissue.
• Develop algorithms for reconstructing virtual histopathology images from sparse phase-contrast CT.
• Compare with standard histology and assess algorithm performance.
• Present results at conferences and internal workshops; publish work.
• Support teaching activities of the professorship.

Kenntnisse

Computer vision

Machine learning

X-ray imaging

Scientific computing

English communication

Ausbildung

Master's degree in physics, engineering or computer science

Tools

Python

Jobbeschreibung

ETH Zurich’s X-ray Imaging Professorship seeks a Doctoral Student to advance translational imaging, focusing on machine-learning-based sparse 3D image reconstruction for histopathology of breast tissue biopsies using X-ray phase-contrast radiography and tomography.

You will contribute to data pipelines, algorithm development, and dissemination, while participating in multidisciplinary studies with clinical partners.