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

Applications for this vacancy closed on 22 November 2024 at 12:00PM
<div xmlns="http://www.w3.org/1999/xhtml"> <p></p><div>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.</div><br> <div>&#160;</div><br> <div>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.</div><br> <div>&#160;</div><br> <div>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.</div><br> <div>&#160;</div><br> <div>The post is funded by UKRI - Engineering and Physical Sciences Research Council (EPSRC) grant &#8220;Artificial Intelligence X-ray Imaging for Sustainable Metal Manufacturing (AIXISuMM)&#8221; and is&#160;fixed-term for up to 2 years.</div><br> <div>&#160;</div><br> <div>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.</div><br> <div>&#160;</div><br> <div>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. &#160;<strong>Please do not attach any manuscripts, papers, transcripts, mark sheets or certificates as these will not be considered as part of your application.</strong></div><br> <div>&#160;</div><br> <div>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.</div> </div>
dc:spatial
Department of Materials, Begbroke Science Park, Oxford
Subject
oo:contact
oo:formalOrganization
oo:organizationPart
vacancy:applicationClosingDate
2024-11-22 12:00:00+00:00
vacancy:applicationOpeningDate
2024-10-24 09:00:00+01:00
vacancy:internalApplicationsOnly
False
vacancy:salary
type
comment
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 ...

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 ...
label
Postdoctoral Research Assistant in Artificial Intelligence X-ray imaging for sustainable metal manufacturing
notation
176034
based near