Postdoctoral Research Associate in Machine Learning For 3D Imaging in Electron and X-Ray Microscopy

University of Cambridge

United Kingdom

We are inviting applications for a Post-Doctoral Research Associate (PDRA) position in machine learning for 3D imaging with electron & X-ray microscopy at the University of Cambridge. This project aims to combine state-of-the-art multimodal and multidimensional electron and X-ray microscopy with machine learning methods for the acquisition and analysis of complex terrestrial and extraterrestrial materials.

The main research strand of this project will involve the development of experimental and analysis tools for automated mineralogy based on spectral decomposition and multimodal analysis of electron and X-ray data. The secondary strand is to employ these tools in multimodal segmentation of 3D X-ray tomography datasets. The project is part of the EXCITE 'starting community' funded by Horizon 2020, which brings together 15 leading institutions across Europe to develop and utilise electron and X-ray imaging capabilities. As such, the PDRA will be embedded within this research network with extensive opportunities for external collaboration, including playing a leading role the transnational instrument access programme. The PDRA will also be encouraged to demonstrate the capabilities of the methodologies developed in the context of their own research.

In Cambridge, the PDRA will be hosted jointly by the Department of Earth Sciences and Department of Materials Science and Metallurgy under the guidance of Prof. Richard Harrison, Prof. Paul Midgley, Dr. Emilie Ringe and Dr. David Wallis. The PDRA will have access to the outstanding microscopy facilities and communities of both departments.

Applicants must have a working knowledge of transmission electron microscopy and should have experience in electron imaging and tomography, focused ion beam, and/or X-ray imaging. Applicants should also have experience with machine learning and proficiency in Python programming would be highly beneficial. The successful candidate must have (or be about to obtain) a relevant PhD and will have good communication skills.

Fixed-term: The funds for this post are available for 3 years from May 2021.

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Interested candidates should contact Prof. Richard Harrison ( for more information about the position. Should you have any questions about the application process, please contact

Please quote reference LB25996 on your application and in any correspondence about this vacancy.

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