Postdoctoral Research Assistant in Artificial Intelligence X-ray imaging for sustainable metal manufacturing

We are seeking an outstanding candidate to work in the Process Dynamics group
on understanding how impurities and/or additions to liquid metal alloys can be
used to control the final microstructure and defects.





The successful candidate will work on the design and undertaking of real-time
in-situ X-ray imaging solidification experiments to investigate the dynamics
of crystal formation both using laboratory and synchrotron sources. The work
will initially focus on the analysis of existing X-ray imaging data of the
solidification of aluminium alloys and develop novel multi-modal imaging
methodologies for the investigation of aluminium and steel solidification.
Post-solidification measurement of key microstructural features using various
microscopy and other techniques will also be performed. The post holder will
closely collaborate with other scientists and technicians from the group and
the other project partners. The post is fixed-term for two years and based in
the Department of Materials at its Begbroke Science Park site, 5 miles north
of Oxford.





The appointed person will be an experimental materials scientist or process
engineer with experience in X-ray imaging of solidification or related
analytical approach and a doctorate (or be near completion) in materials
science or a relevant engineering or physical sciences discipline. Hands-on
experience in developing and building bespoke experimental rigs and carrying
out experiments in a synchrotron environment is preferred. The appointed
person will require programming skills and experience in computer vision
techniques, preferably in Python, for the development of semi and fully
automatic data analysis algorithms.





The post is funded by UKRI - Engineering and Physical Sciences Research
Council (EPSRC) grant “Artificial Intelligence X-ray Imaging for Sustainable
Metal Manufacturing (AIXISuMM)” and is fixed-term for up to 2 years.





The vision of AIXISuMM is that transformative and efficient technologies to
manufacture high-grade recycled metal alloys from low-grade scrap sources can
be delivered by uncovering the missing science to engineer the solidification
microstructure to tolerate higher level of impurities, by leveraging the
combined power of multi-modal X-ray imaging and in-line artificial
intelligence (AI). The project also involves the Detector Development Group at
the Science and Technology Facilities Council (STFC) and Loughborough
University together with a group of industry partners.





All applications must be made online using the Oxford University E-Recruitment
system, no later than 12 noon on 22 November 2024. You will be required to
upload a CV and a Supporting Statement as part of your application. **Please
do not attach any manuscripts, papers, transcripts, mark sheets or
certificates as these will not be considered as part of your application.**





Interviews are scheduled to take place at the Department of Materials week
commencing 9 December 2024 and you must be available during this time, either
by Teams, Zoom or in person. Please note in normal circumstances only
interview travel expenses within the UK will be reimbursed.