£46,049 Per year
Undetermined
Undetermined
Coventry, England, United Kingdom
Summary: The Research Fellow will contribute to the UKRI project “AC/DC: Accessible CT Data Compression,” focusing on developing domain-specific image data compression methods using AI and machine learning. The role requires expertise in coding, particularly in C/C++, to create encoder/decoder software for compressed data. The position involves collaboration with prestigious partners and includes a secondment to the University of Cambridge. The successful candidate will help reduce data storage requirements significantly, benefiting global research infrastructure.
Key Responsibilities:
- Develop domain-specific compression methods for image data using AI and machine learning.
- Create encoder/decoder software for compressed data in C/C++.
- Focus on lossless compression and identify stronger compression ratios through machine learning.
- Integrate AI-supported lossy methods into user-friendly open-source software.
- Collaborate with project partners and participate in a two-month secondment to the University of Cambridge.
Key Skills:
- Experience in image data compression and AI/machine learning.
- Proficiency in Python and C/C++ programming.
- Understanding of existing image and video codecs.
- Ability to identify patterns in data and adapt methodologies for specific datasets.
- Previous experience in software creation and management.
Salary (Rate): £46,049.00 yearly
City: Coventry
Country: United Kingdom
Working Arrangements: undetermined
IR35 Status: undetermined
Seniority Level: undetermined
Industry: Other
About The Role
Informal Queries
For informal queries, please contact Jay Warnett, Associate Professor (Reader), at j.m.warnett@warwick.ac.uk
Flexible Working
We will consider applications for employment on a part-time or other flexible working basis (e.g. job share), despite the position being advertised as full-time.
We are seeking to appoint a Research Fellow to play a crucial role in our recently UKRI awarded project “AC/DC: Accessible CT Data Compression”. This candidate will have a background in image data compression, supported by experience with AI and machine learning. They will utilise this knowledge to develop domain specific compression by exploiting spatial and temporal redundancies, including through implementation of AI. They will also create the encoder/decoder software for compressed data, so require experience of coding these structures in C/C++.
X-ray Computed Tomography enables non-destructive observation of an objects internal structure. From material phases of novel alloys to uncovering a fossils provenance it supports a broad spectrum of academic research. However, even modest operation of a single system generates >10TB of raw data annually which requires archiving for 10+ years. This had led to an unsustainable data accumulation globally, desperate for a solution. This project will create the first accessible, domain specific, machine independent CT data compression methods. Your experience with image data compression structures combined with intuition of domain specific redundancies will enable us to develop such methods, slashing storage requirements by up to 80% and directly lowering the carbon footprint of global research infrastructure. You will initially focus on lossless compression with predictor models and inspiration from video encoding. Stronger compression ratios will be identified through machine learning and AI methodologies. Subsequently, AI supported lossy methods will be developed with a focus on optimal compression with minimal acceptable data loss. These methods will be integrated into user friendly open-source compression software so everyone can benefit. The project is joint with University of Cambridge and University of Portsmouth. It includes an annual two month secondment to Cambridge with all travel covered, to receive the experience of multiple research environments to develop the best data compression. There are a series of project partners including NASA, Rolls-Royce, and JLR who will be appraising the research as it evolves, ensuring the outcomes are exploited.
About You
An experienced data compression engineer with experience in AI and machine learning. A keen interest in identifying patterns in data, and learning from fields adjacent to their knowledge. This position requires an understanding of existing image and video codecs, with an intuition of how they would be adapted specifically for these datasets. AI methodologies for compression will be a key focus to identify further refinements. Previous experience in creating software and management thereof is required. The candidate must have Python and C/C++ programming experience. No previous experience with X-ray Imaging is necessary.
For details on the experience and skills required, please refer to the job description attached as a PDF below.
PhD Status
If you are near submission of your PhD, or have not yet had it conferred, any offers of employment will be made at Research Assistant level, at the highest spinal point of pay grade 5 (£34,610 per annum). Upon receipt of evidence confirming the successful award of your PhD, you will be promoted to Research Fellow , at the lowest spinal point of grade 6 (£35,608 per annum).
About The Department
CiMAT (Centre for Imaging, Measurement and Additive Techonologies) has been developing X-ray Imaging methodologies for over 20 years. The group is part of the National Facility in X-ray CT, making the technique more widely accessible for researchers. We have five X-ray CT scanners on site to support a variety of imaging needs, participating in collaborative academic and industrial research, making it one of the largest facilities of its kind. The Warwick Manufacturing Group (WMG) is the largest department at the University of Warwick, with over 800 staff and nearly 3,000 students across undergraduate and postgraduate programmes in management, technology, and applied engineering. We are globally recognised for our world-class research, innovative industry partnerships, and teaching excellence, and we are proud holders of the Athena SWAN Silver Award and the Institutional Silver Award. Find out more about the High Value Manufacturing Catapult centre. Find out more about the Energy Innovation Centre. Find out more about our range of undergraduate and apprenticeship degrees here.
About The University
We are a world-leading research-intensive university founded in 1965. We are ranked 74th in the world and 9th in the UK. * Additionally, 92% of our research is rated world-leading or internationally excellent .** Find out more about us at warwick.ac.uk/about/. World University Ranking 2026, Complete University Guide 2026 Research Excellence Framework 2021
How to Apply
CLOSING DEADLINE: Sunday 24th May 2026 at 11:55pm (UK Time)
To apply, please click APPLY below and submit your application by the closing deadline. You will be asked to include a CV and cover letter. Within these documents, please:
- Outline your employment and education history (including your most recent employment).
- Outline the reasons for your interest in this position.
- Demonstrate how you meet the requirements of the role with clear reference to each of the essential and desirable criteria in the Job Description (PDF attached below).
Interview Date: To be confirmed
Start Date: 1st September 2026
Applications must be submitted by the closing deadline. Only applications submitted through our Careers Portal () will be considered. You are welcome to include any careers breaks you may have taken (e.g. parental/caring/long-term sick leave). Please note that if you do not evidence the essential criteria, the hiring panel may not be able to shortlist your application. For guidance on how to format a cover letter, see here.
What we Offer
We Provide a Comprehensive Range Of Benefits, Including
- An attractive pension scheme.
- 30 days holiday plus University Christmas closure.
- Generous parental/adoption leave policy.
- Onsite childcare facilities.
- Excellent learning and development opportunities.
We recognise the importance of a healthy work/life balance and offer access to flexible working arrangements. For more information, see here.
We are proud to be a Living Wage employer.
Our Commitment to Inclusion
Equality, Diversity, & Inclusion
Warwick is committed to fostering a diverse, inclusive and respectful community where everyone can thrive. We welcome applications from all backgrounds, cultures, and communities, and actively encourage candidates from underrepresented groups to apply. Find out more about our Social Inclusion work at Warwick. Find out more about our awards and accreditations. We are also one of the six founder institutions of the EUTOPIA European University Alliance.
Safeguarding & DBS
The University of Warwick is committed to safeguarding and promoting the welfare of all those we work with. Roles involving regulated activity are subject to a Disclosure and Barring Service (DBS) check at the appropriate level, in line with the DBS Code of Practice. The University will ensure that anyone subject to a barring order does not undertake any work with the barred group (children and/or adults). All employees, volunteers, and partners are expected to share our commitment to safeguarding.
Rehabilitation of Ex-Offenders
The University will not discriminate against applicants who make a disclosure relating to a conviction. Disclosures at application stage are only visible to the DBS team, not to hiring panels. This ensures fairness and removes bias from the shortlisting process.
Job Description JD - Research Fellow (111308).pdf – 166KB Opens in a new window
Right to Work in the UK
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