Project Overview
| Opportunity | Doctoral Position in Sparse Reconstruction of Virtual Histology Images at ETH Zurich |
| Host | ETH Zurich |
| Location | Zurich, Switzerland |
| Study Level | PhD |
| Funding | Fully Funded, stipend provided, tuition covered |
| Stipend | Fully funded doctoral position at ETH Zurich. Amount not specified. |
| Application Deadline | Open until filled |
| Apply | Official application page ↗ |
About the Position
The X-ray Imaging Professorship develops advanced imaging techniques at the synchrotron and strives at the translation of novel imaging approaches to medical devices in a multidisciplinary effort involving academia, industry and medical partners. The Paul Scherrer Institute PSI is the largest research institute for natural and engineering sciences within Switzerland. We perform research in the fields of matter and materials, energy and environment and human health.
We are seeking a highly motivated Doctoral Student to join our team in translational X-ray imaging and contribute to the development of X-ray imaging technology that can significantly improve the treatment and outcome of oncological patients.
Project Background
You will contribute to the design and implementation of machine-learning-based sparse 3D image reconstruction modalities to be used for fast histopathological assessment of tumor biopsies with X-ray phase-contrast radiography and tomography. As part of our multidisciplinary team of academic and clinical researchers, you will be involved in ongoing pilot studies at cantonal hospitals and have the chance to contribute directly to the improvement of clinical workflows and benefit cancer patients and health care professionals.
Job Description
- Collection of grating interferometry X-ray phase contrast microCT data of breast tissue biopsies
- Setup of data pipelines for synchrotron and laboratory microCT scans of soft tissue
- Develop algorithms for reconstruction of virtual histopathology images from sparse phase-contrast CT acquisitions of oncological specimens
- Comparison with standard histology and assessment of algorithm performance
- Present results at international conferences as well as internal workshops
- Summarize your results in scientific publications
- Support the professorship in teaching activities
Profile
- Excellent qualifications with a university degree (Master or equivalent) in physics, engineering or computer science
- Proficiency in computer vision and machine learning with Python
- Knowledge of X-ray physics and laboratory experience in imaging would be a benefit
- Highly self-motivated, curious and committed character
- Well organized
- Willingness to conduct research in a multidisciplinary team
- Excellent communication skills in English (written and spoken)
We Offer
- Our organization operates on the principles of interdisciplinary collaboration, innovation, and dynamism.
- Comprehensive on-the-job training, as well as access to various personal and professional development opportunities.
- A strong culture of vocational training, which will enable you to enhance your skillset and advance your career.
- Modern employment conditions and on-site infrastructure to support work-life balance.
Application Requirements
Submit online application with the following documents:
- Motivation letter
- CV
- Publication List
- Transcripts
- Ideally two reference letters
Applications are exclusively accepted through the online application portal. Applications via email or postal services will not be considered.
Contact
- Email: stampanoni@biomed.ee.ethz.ch
- Email: gianluca.iori@psi.ch
Questions about this position, eligibility or the application process should be sent to the contacts above or raised through the channel given on the official announcement page.
Official Link
https://www.jobs.ethz.ch/job/view/JOPG_ethz_pGJRE5rDAavyV6eLYI
Important Notes
- This is a full-time, fixed-term position (100%, Zurich).
- Applications evaluated on a rolling basis until position is filled.
- Multidisciplinary collaboration between ETH Zurich, Paul Scherrer Institute (PSI), and cantonal hospitals.
- Excellent opportunity for translational medical imaging research with direct clinical impact.
About ETH Zurich
ETH Zurich is Switzerland's federal institute of technology in Zurich. It offers undergraduate, master's and doctoral education across engineering, natural sciences, mathematics, architecture and related disciplines. Its research connects fundamental scientific questions with technological applications, supporting international collaboration and training for students interested in advanced study, innovation and scientific discovery.
Official website: https://ethz.ch
How to Apply
Submit your application through the official portal before the deadline: Open until filled. Read the eligibility requirements carefully and prepare all requested documents — early applications are strongly recommended for competitive awards.
Open the official application page ↗
Application guides
Frequently asked questions
Drawn from this listing's own record. Always confirm the details on the official source before applying.
What is the deadline for Doctoral Position in Sparse Reconstruction of Virtual Histology Images at ETH Zurich?
Applications for this listing stay open on a rolling basis — there is no fixed closing date (Open until filled). Apply early: rolling awards are often confirmed in the order applications are received.
Is Doctoral Position in Sparse Reconstruction of Virtual Histology Images at ETH Zurich fully funded?
This is a fully funded award: tuition is covered and a living stipend is provided for the duration of the programme. CHF 53,500–73,100/year gross depending on rate (ETH Zurich scale, 2026).
Who is eligible to apply for Doctoral Position in Sparse Reconstruction of Virtual Histology Images at ETH Zurich?
This opportunity is open to applicants worldwide. Host-country status is not a requirement, although you must still satisfy the visa rules for Switzerland. Applications are assessed by ETH Zurich.
How do I apply for Doctoral Position in Sparse Reconstruction of Virtual Histology Images at ETH Zurich?
Applications for Doctoral Position in Sparse Reconstruction of Virtual Histology Images at ETH Zurich are submitted directly to ETH Zurich through the provider's own application portal — use the Apply button on this page to open it. NextApply does not process applications or charge a fee.
Is an English proficiency test required for Doctoral Position in Sparse Reconstruction of Virtual Histology Images at ETH Zurich?
Yes — an English-language certificate is required for this listing. Check the exact band expected on the official source, since it can differ by programme. Requirements for Switzerland are published by the provider.
What study level does Doctoral Position in Sparse Reconstruction of Virtual Histology Images at ETH Zurich offer?
This listing is offered at PhD level. That describes the qualification on offer, not a credential you must already hold — check the provider's stated entry requirements before applying.