Marco Stampanoni
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Doctoral Position in Sparse Reconstruction of Virtual Histology Images ETH Zürich in Switzerland
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Country
Switzerland
University
ETH Zürich
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About this position
ETH Zürich is offering a doctoral position in sparse reconstruction of virtual histology images within the X-ray Imaging Professorship and its translational imaging environment at the Paul Scherrer Institute (PSI). The project sits at the intersection of synchrotron-based imaging, machine learning, and medical translation, with a strong focus on improving histopathological assessment of tumor biopsies and supporting better outcomes for oncological patients.
The successful doctoral researcher will contribute to the design and implementation of machine-learning-based sparse 3D reconstruction methods for fast virtual histology using X-ray phase-contrast radiography and tomography. The work is embedded in a multidisciplinary team of academic and clinical researchers, with exposure to ongoing pilot studies at cantonal hospitals and opportunities to contribute to clinical workflow improvement in cancer diagnostics.
Core research tasks include collecting grating-interferometry X-ray phase-contrast microCT data from breast tissue biopsies, building data pipelines for synchrotron and laboratory microCT scans of soft tissue, and developing reconstruction algorithms for virtual histopathology from sparse phase-contrast CT acquisitions of oncological specimens. The project also includes comparing outputs with standard histology, evaluating algorithm performance, presenting results at conferences and workshops, and publishing scientific results.
Applicants should hold a Master’s degree or equivalent in physics, engineering, or computer science. Strong skills in computer vision, machine learning, and Python are expected. Knowledge of X-ray physics and laboratory imaging is considered an advantage. The position also values high motivation, curiosity, strong organization, commitment to collaborative work, and excellent English communication skills.
ETH Zürich highlights its culture of interdisciplinary collaboration, innovation, sustainability, and diversity. The role comes with on-the-job training, professional development opportunities, and modern employment conditions in a supportive research environment. Applications must be submitted online and should include a motivation letter, CV, publication list, and transcripts; ideally, candidates should also provide two reference letters.
For questions about the position, applicants may contact Prof. Dr. Marco Stampanoni at [email protected] or Dr. Gianluca Lori at [email protected]. The application deadline is not specified in the posting.
Funding details
Available
What's required
A university degree at Master level or equivalent in physics, engineering, or computer science is required. Applicants should have proficiency in computer vision and machine learning with Python. Knowledge of X-ray physics and laboratory imaging experience is beneficial. The role requires a highly self-motivated, curious, committed, and well-organized person who is willing to work in a multidisciplinary team and communicate fluently in English, written and spoken.
How to apply
Apply online through the ETH Zurich application portal. Submit a motivation letter, CV, publication list, and transcripts; ideally also include two reference letters. Do not apply by email or post.
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