Doctoral Position in Sparse Reconstruction of Virtual Histology Images
Develop machine-learning-based 3D image reconstruction for fast histopathological assessment of tumor biopsies using X-ray phase-contrast radiography.
Best for:Best for candidates with a Master’s in physics, engineering, or computer science, skilled in Python-based machine learning and computer vision, and eager to contribute to translational medical imaging research.
Overview
This doctoral position at ETH Zurich’s X-ray Imaging Professorship focuses on advancing X-ray imaging technology to improve oncological patient treatment. The successful candidate will design and implement machine-learning algorithms for sparse 3D image reconstruction, enabling rapid virtual histopathology assessments of tumor biopsies. The project involves data collection at synchrotrons and laboratories, algorithm development, clinical validation, and collaboration with multidisciplinary teams. The role is ideal for candidates with a strong background in physics, engineering, or computer science, particularly those with expertise in computer vision, machine learning, and X-ray physics. The position is based at the Paul Scherrer Institute (PSI) and offers a collaborative, interdisciplinary environment with direct clinical impact.
What you'll do
- Collect grating interferometry X-ray phase-contrast microCT data of breast tissue biopsies for analysis.
- Develop and set up data pipelines for synchrotron and laboratory microCT scans of soft tissue samples.
- Design and implement machine-learning-based algorithms for sparse 3D image reconstruction of virtual histopathology images.
- Compare algorithm performance with standard histology methods and assess clinical applicability.
- Present research findings at international conferences and internal workshops.
- Publish results in peer-reviewed scientific journals.
- Support teaching activities within the professorship.
Requirements
Degree required: Master’s degree or equivalent in physics, engineering, or computer science
Degree offered: PhD
Language: English; proficiency in spoken and written English required
Instruction: English
- Proficiency in computer vision and machine learning using Python
- Experience with X-ray physics and laboratory imaging techniques
- Strong analytical and problem-solving skills
- Ability to work collaboratively in multidisciplinary teams
- Excellent written and spoken English communication skills
- No specific nationality or residency restrictions mentioned
- Open to applicants with a Master’s degree or equivalent
Funding & terms
How to apply
Applicants must submit their application through the ETH Zurich online application portal. Required documents include a motivation letter, CV, publication list, transcripts, and ideally two reference letters. Applications via email or postal services will not be considered.
- Motivation letter
- CV
- Publication list
- Transcripts
- Two reference letters (ideally)
Contact
Prof. Dr. Marco Stampanoni / Dr. Gianluca Lori· Supervisors
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