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- Postdoctoral Researcher in X-ray Imaging and Machine Learning for Advanced Manufacturing
Postdoctoral Researcher in X-ray Imaging and Machine Learning for Advanced Manufacturing
LUNDS UNIVERSITETSkåne län, Lund
Previous experience is desired
30 days left
to apply for the job
Lund University was founded in 1666 and is consistently ranked among the world's leading universities. We have approximately 46,000 students and 8,500 staff members in Lund, Helsingborg, and Malmö. We are united in our strive to understand, explain, and improve our world and the conditions of people.
Specific Department Description
The Department of Synchrotron Light Physics (http://www.sljus.lu.se (http://www.sljus.lu.se)) is part of the Department of Physics and has more than 40 employees. The research focus is on experimental studies of the electronic, structural, and chemical properties of materials. At the department, we use and develop a wide range of synchrotron and lab-based techniques. We are also involved in developing beamlines, experimental stations, experimental techniques, and accelerator systems for the MAX IV Laboratory, and we have a close connection to the European Spallation Source (www.esss.se (http://www.esss.se)), a new European neutron facility under construction adjacent to MAX IV. MAX IV is a national large-scale laboratory that is part of Lund University and is within cycling distance from the Department of Physics. The laboratory is the world's brightest synchrotron light source, where researchers from Sweden and the rest of the world conduct research in fields such as materials science, biology, chemistry, and nanotechnology. The Department of Medical Radiation Physics (www.msf.lu.se (http://www.msf.lu.se)) is interdisciplinary and has research divisions covering all aspects of medical physics, such as radiology, radiotherapy, mathematics and physics for medical image processing, nuclear medicine, and magnetic resonance. Environmental radiology, biological effects of radiation, and radiation protection for ionizing and non-ionizing radiation are other important areas of scientific interest.
For more information about the principal supervisor of the project, please refer to: https://portal.research.lu.se/en/persons/pablo-villanueva-perez (https://portal.research.lu.se/en/persons/pablo-villanueva-perez).
Job Responsibilities
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 Multiprojection Imaging (XMPI), synchrotron radiation, and physics-informed machine learning, the project aims to achieve volumetric imaging speeds that are two to three orders of magnitude faster than current state-of-the-art methods.
X-rays have a unique ability to examine samples in their natural state, such as cells, proteins in solution, or electronic devices, potentially with 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 up a completely new spectrum of applications due to their unmatched brilliance. This project aims to enable new spatiotemporal limits in time-resolved imaging while advancing manufacturing at previously unattainable speeds.
The candidate will specifically (i) work on the development of new methods for fast X-ray imaging based on X-ray Multiprojection Imaging, a technique being established at MAX IV, (ii) contribute to the understanding of fast processes in additive manufacturing using new 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 new reconstruction algorithms to retrieve 4D (3D + time) datasets obtained with advanced X-ray imaging techniques. Such reconstruction algorithms involve combining state-of-the-art deep learning methods with physical knowledge of the processes studied and the formation of X-ray imaging.
The developed methods and algorithms will be tested, validated, and implemented 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 collaborations with leading synchrotron facilities and research institutes in Europe. More specifically, the project is framed within an international collaboration between ETH Zurich (Switzerland), Paul Scherrer Institute (Switzerland), and Lund University (Sweden).
The project is experimental with a computational component. The successful candidate will have the opportunity to:
- Contribute to the development of X-ray multiprojection imaging, a technique that can provide volumetric information 3 orders of magnitude faster than state-of-the-art time-resolved 3D imaging at synchrotron facilities.
- Apply XMPI for fast dynamics in advanced manufacturing.
- Develop new acquisition methods and settings for fast 3D imaging.
- Develop new algorithms to reconstruct high-speed 4D datasets by combining physical knowledge and state-of-the-art deep learning methods.
- Be part of an international collaboration to contribute to the understanding of key processes in advanced manufacturing through a new method.
The successful candidate will have opportunities to build an international network, lead beamtime experiments, supervise students, publish in high-impact journals, and develop an independent research profile.
The main duty of the postdoctoral position is to conduct research. Teaching may be included in the duties, but no more than one-fifth of the working time. Within the scope of the employment, there will be an opportunity for three weeks of university pedagogy education.
Qualifications
Eligible for employment as a postdoctoral researcher is someone who has completed a doctoral degree, or a foreign degree assessed as equivalent to a doctoral degree, within the subject area of the employment, and which was completed no more than three years prior to the date of the employment decision. If there are special reasons, the doctoral degree may have been completed earlier.
Other Requirements:
- Very good knowledge of English, both spoken and written.
- The subject of the doctoral degree should be physics, technical physics, applied mathematics, computer science, materials science, mechanical engineering, or a closely related field.
For more information about the position, follow the link: https://lu.varbi.com/what:job/jobID:944018/ (https://lu.varbi.com/what:job/jobID:944018/)
Open to All
We focus on your competence, not your other prerequisites. We are open to adapting the role or workplace to your needs.
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