Fixed-term: The funds for this post are available for 12 months in the first instance.
The Department of Computer Science and Technology is an academic department that encompasses computer science along with many aspects of engineering, technology and mathematics. We have a world-wide reputation for academic research with consistent top research ratings. The Department has an open and collaborative culture, supporting revolutionary fundamental computer science research, strong cross-cutting collaborations internally and externally, and ideas which transform computing outside the University. Please follow the link at: https://www.cst.cam.ac.uk to find out more about our Department.
We invite applications for a Research Associate position on a project focused on the quality of HDR gaming content. The project aims to develop a novel video quality metric and analysis framework that explains perceptual differences between HDR and SDR versions of the same content, particularly when viewed on HDR displays. This work will involve building a large-scale, publicly available dataset of high-dynamic-range gaming content and designing perceptually grounded evaluation protocols. The successful candidate will contribute to cutting-edge research building on ColorVideoVDP and its ML extensions, with outputs including open-source software (MIT license) and high-impact publications. The role also includes collaboration with Sony Interactive Entertainment, including a potential internship in their London office to support subjective studies and model calibration on internal datasets.
This position offers an opportunity to work at the intersection of perceptual modelling, graphics, and machine learning, contributing to both academic research and real-world applications in gaming and streaming technologies.
Essential requirements:
Candidates should hold, or be close to obtaining, a PhD in computer science, electronic engineering, or a closely related discipline, with demonstrated experience and interest in image and video quality assessment, or equivalent research or industry experience. A strong foundation in machine learning and image processing is essential, along with hands-on experience using deep learning frameworks such as PyTorch and excellent programming skills.
Desirable skills:
The ideal candidate will also have advanced training in computer graphics, colour science, high dynamic range imaging, image processing, and video compression.
Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.
This position can be filled by an appropriate candidate at a Research Assistant (post-doc) or Research Associate (pre-doc) level, depending on relevant qualifications and experience. An appointment at a research associate level is dependent on having a PhD (or equivalent experience). Where a PhD has yet to be awarded, an appointment will initially be made as a research assistant and amended to research associate when the PhD is awarded.
Please contact Dr Rafal Mantiuk (http://www.cl.cam.ac.uk/~rkm38/, [email protected] with any informal queries regarding the post. Please include the number NR50154 in your email.
Please ensure you upload your curriculum vitae; a statement of the particular contribution you would like to make to the project (maximum 500 words); a description (max 1 page of A4) of the research project you are most proud of and your contribution to it (provide a link to github repository, if available); a transcript of your university grades; and a cover letter with details of your visa status and earliest possible starting date. The track record of publications should be included in the application as a link to Google Scholar or an ORCID profile. If you upload any additional documents that have not been requested, we will not be able to consider them as part of your application.
Please include the number NR50154 in your email on your application and in any correspondence about this vacancy.
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