Vacant job

Postdoctoral Researcher in Machine Learning Applied to X-ray Microtomography for 4D Material Analysis

Lund University was founded in 1666 and is consistently ranked among the world's top universities. There are approximately 47,000 students and more than 8,800 employees in Lund, Helsingborg, and Malmö. We unite in our efforts to understand, explain, and improve our world and the conditions of humanity.

Lund University welcomes applicants from diverse backgrounds and experiences. Gender equality, equal opportunities, and diversity are fundamental principles for all parts of our operations.

Workplace Description

The Department of Solid Mechanics was the first department established at LTH and is now part of the Faculty of Engineering. The department operates in an international environment and has contacts with research organizations and companies both nationally and internationally. Today, the Department of Solid Mechanics consists of about 25 employees, of which approximately 15 are PhD students. The work climate is open and welcoming, striving to provide every employee with the opportunity to develop personally and professionally.

The subject of solid mechanics deals with methods and principles for describing deformable bodies. Solid mechanics is a fundamental subject within mechanical engineering and is of basic importance to related disciplines. The problems and questions addressed within solid mechanics have clear relevance to industrial applications.

Research in solid mechanics at LTH is specifically focused on constitutive mechanics, numerical methods, microstructural mechanics, structural optimization, and experimental methods. The department also has a strong activity in X-ray and neutron methods for materials research.

Project Description

The postdoctoral position will be part of the AI-Tomo project, funded by the Swedish research funding agency Vinnova. The project has been established to support and develop the use of machine learning tools to accelerate the analysis of tomographic data at the MAXIV synchrotron. The MAXIV synchrotron facility (maxiv.lu.se) is a world-leading facility for materials research located in Lund. Currently, there are three beamlines offering X-ray tomography. The project is a collaboration between the Department of Solid Mechanics at Lund University, MAXIV, RISE (Research Institutes of Sweden), Tetra Pak, and Billerud.

You will conduct research and development activities related to the development of 3D/4D image quantification methods and pipelines using machine learning tools. The employment will be at the Department of Solid Mechanics at Lund University, and the work will be carried out in collaboration with RISE, MAXIV, Tetra Pak, and Billerud.

Responsibilities

The primary responsibility of the postdoctoral researcher will be to conduct research. Teaching may also be included in the responsibilities, but no more than one-fifth of the working time. Within the framework of the employment, there is an opportunity for three weeks of higher education pedagogical training. The purpose of the position is to develop independence as a researcher and create conditions for further qualification.

The position will primarily involve research related to the development of machine learning tools for analyzing tomographic data from the MAXIV synchrotron to understand material structures and their evolution. A key focus will be on 4D data from in-situ experiments utilizing X-ray microtomography to monitor material development during, for example, mechanical loading or liquid infiltration.

You will be part of a dynamic, international team involved in experimental mechanics and 3D imaging at the Department of Solid Mechanics. You will also be part of the strong international research environment at MAXIV and play a key role in developing the tomography user community around the facility.

Eligibility

To be eligible for the postdoctoral position, the applicant must have obtained a doctoral degree, or a foreign degree deemed equivalent to a doctoral degree, in the relevant field of employment. Proof of meeting the eligibility requirement must be submitted no later than at the time the employment decision is made. Primarily, the applicant should have obtained their degree no more than three years before the application deadline. If there are special reasons, the doctoral degree may have been obtained earlier.

Other Requirements:

• Excellent knowledge of English, both spoken and written;
• Significant practical experience in image analysis;
• Knowledge and experience in programming (Python, Matlab, or other languages relevant to image analysis);
• The ability to work both independently and in teams with other researchers and research groups;
• Excellent communication skills.

For the full advertisement, see here (https://lu.varbi.com/se/what:job/jobID:771247/).

LTH – Lund University Faculty of Engineering – is the technical faculty at Lund University. At LTH, we educate people, build knowledge for the future, and work hard to develop society. We create space for brilliant research and inspire creative development in technology, architecture, and design. Nearly 10,000 students study here. Each year, our researchers – many of whom work in world-leading profile areas – publish around 100 theses and 2,000 scientific findings. A number of research results and student projects are refined into innovations. Together we explore and create – for the benefit of the world.

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