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The newly established Laboratory for Nanoscale X-ray Metrology is looking for a motivated PhD student to develop computational and experimental methods for high-resolution 3D imaging. In this role, you will help establish new X-ray microscopy performance benchmarks by pushing the limits of imaging resolution and sample thickness achievable for semiconductor applications. To achieve this, the project will focus on the following topics:

Depth-of-Field Limitations: At 1 nm resolution, the depth of field shrinks to just a hundred nanometers, yet the high X-ray penetration allows imaging of samples that are several orders of magnitude thicker. The project will develop an extended depth-of-field reconstruction framework for thick 3D samples.
Mismatch Between Theory and Experiment: Reconstruction methods are based on idealized image formation models, which break down under extreme imaging conditions. Achieving high-performance imaging requires improving the models and developing robust computational optimization algorithms, to account for issues such as experimental nanoscale vibrations.
High-Performance 3D Imaging: Integrating these methods into tomography and laminography, and performing synchrotron-based experiments to visualize previously "unseen" features in modern semiconductor devices.

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Project Description

The performance of X-ray microscopy has improved significantly over the last decade, enabling synchrotron-based X-ray imaging to resolve individual transistors in modern semiconductor devices. As semiconductor technology enters the new era of the 3D transistor, the need for non-destructive, high-resolution 3D imaging methods has never been greater. While X-ray microscopy holds the potential for nanometer-scale defect detection in 3D semiconductor devices, its imaging performance requires further breakthroughs.

Currently, the highest-performance microscopy tools utilize ptychography—a coherent diffractive lensless imaging technique that replaces the limitations of traditional lenses with sophisticated computational algorithms. However, achieving the ~1 nm 3D resolution required for next-generation semiconductor metrology remains a "grand challenge". At these extreme resolutions, massive photon requirements cause radiation damage, nanoscale mechanical instabilities become severe, and the projection approximation completely breaks down for thick samples.

We offer

This position offers a unique dual environment. You will have the opportunity to earn your PhD through a structured doctoral program at EPFL, one of the world’s leading technical universities. Physically, you and the team will be based at the Swiss Light Source (SLS) synchrotron located at the Paul Scherrer Institute (PSI).

A fully funded 4-year PhD position with competitive salary.
Core involvement in the SNSF Starting Grant project NEXUS-3D, working at the intersection of applied physics, high-performance computing, and semiconductor metrology.
Opportunity to work together with leading synchrotron scientists and computational X-ray imaging experts.
A unique research environment based at a newly upgraded 4th generation synchrotron.
Support for professional development such as attending summer schools, international conferences and conducting experiments at synchrotrons around the world.

Profile

We are looking for a PhD candidate highly motivated to develop computational methods for lensless X-ray microscopy. This position is for you if you bring:

Educational Background: A Master’s degree in Physics, Engineering, Mathematics, Computer Science, or a related field.
Computational Skills: Strong Python proficiency with a drive to develop algorithms for large-scale data reconstruction.
Lensless Imaging: A keen interest in mastering the physics of coherent diffractive imaging and solving inverse imaging problems (e.g., ptychography).
Synchrotron Experiments: Enthusiasm for hands-on research, such as conducting and designing synchrotron X-ray imaging experiments.
Teamwork & Culture: Fluent English and a collaborative, open-minded attitude. You will be working in a diverse, international team spanning a broad range of cultures, genders, and backgrounds.
Bonus: Prior experience with tomography, computational optimization, machine learning, coherent imaging, synchrotron experiments, or high-performance computing (HPC) is a plus.

Informations

Application deadline : 01.07.2026

Activity Rate : 100%

Contract Type: PhD student

Duration: 4 years

Reference: 2224

Pre-screening will start immediately and continue until suitable candidates have been found. The interviews will likely be held around mid-July.

For any further information, please contact Prof. Tomas Aidukas ([email protected]). If you are successful, you will need to enroll in one of the EPFL Doctoral Programs. Please check this page for additional information on admission. Please note that this is a separate application process necessary to be eligible to complete your PhD at EPFL and getting this position is contingent to being accepted in an EPFL doctoral school program.

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