Post-doctoral fellow in Physics; fast time-resolved 3D imaging X-ray multi-projection imaging advanced

Post-doctoral Fellow in Physics;
Fast Time-Resolved 3D Imaging with X-ray Multi-Projection Imaging for Advanced Manufacturing

Lunds universitet, Naturvetenskapliga fakulteten, Fysiska intitutionen

Lund University was founded in 1666 and is repeatedly ranked among the world's top universities. The University has around 46 000 students and 8 500 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

The Division of Synchrotron Radiation Research is a part of the Department of Physics and has more than 40 employees. The focus of the research is on experimental studies of electronic, structural, and chemical properties of materials. The Division is developing a new activity focusing on magnetic properties. At the Division, we use and develop a wide range of large facility- and lab-based techniques.

We are additionally engaged in the development of the MAX IV Laboratory in the fields of beamlines, experimental stations, techniques for Synchrotron radiation, and accelerator systems. MAX IV is a national large-scale research laboratory hosted by Lund University and situated within biking distance from the Department of Physics. It provides scientists from Sweden and the rest of the world with the most brilliant Synchrotron radiation source and instrumentation for research in areas such as materials science, structural biology, chemistry, and nanotechnology.

This project aims to develop next-generation X-ray imaging methods capable of capturing 3D processes in real time during advanced manufacturing. By combining X-ray multi-projection imaging, synchrotron radiation, and physics-informed machine learning, the project seeks to achieve volumetric imaging rates two to three orders of magnitude faster than current state-of-the-art approaches.

X-rays have a unique ability to investigate samples in their natural state, such as cells, proteins in solution, or electronic devices, potentially at resolutions up to the atomic level. The advent of diffraction-limited storage rings (MAX IV) and X-ray free-electron lasers (European XFEL) has opened a whole new spectrum of applications due to their unprecedented brilliance. This project aims to enable new spatiotemporal frontiers in time-resolved imaging while advancing manufacturing at previously unattainable speeds.

In particular, the candidate will (i) work on the development of novel methodologies for fast X-ray imaging based on X-ray multi-projection imaging, a technique being established at MAX IV, ii) contribute to the understanding of fast processes in additive manufacturing with novel methodology to enable 4D imaging two to three orders of magnitude faster than state-of-the-art techniques, and iii) contribute to the development of novel reconstruction algorithms to retrieve 4D (3D + time) datasets acquired using advanced X-ray imaging techniques.

Such reconstruction algorithms entail merging state-of-the-art deep learning approaches with physical knowledge of the studied processes and X-ray imaging formation.

The developed approaches and algorithms will be tested, validated, and commissioned primarily at MAX IV (Sweden), as well as at ESRF-EBS (France) and SLS 2.0 (Switzerland).

The project includes opportunities for international travel and collaboration with leading synchrotron facilities and research institutes in Europe. Specifically, the project is framed within an international collaboration among ETH Zurich (Switzerland), the Paul Scherrer Institute (Switzerland), and Lund University (Sweden), including a planned 1–2 month research stay at PSI.

The project is experimental with a computational component. The successful candidate will have the opportunity to:

• Contribute to the development of X-ray multi-projection imaging, a technique capable of providing volumetric information 3 orders of magnitude faster than state-of-the-art time-resolved 3D imaging at synchrotron facilities.
• Apply XMPI to fast dynamics in advanced manufacturing.
• Develop new acquisition approaches and setups for fast 3D imaging.
• Develop novel algorithms for reconstructing…