Fixed-term: The funds for this post are available for 3.5 years.
Applications are invited for a PhD studentship in display quality. The goal is to develop algorithms for automated assessment of the quality of electronic displays (OLED, LCD, and others) when presenting typical video content. The algorithms may combine machine learning techniques with models of displays and human vision to predict quality with respect to a given display (resolution, size, peak luminance, refresh rate and others) and viewing conditions (viewing distance, ambient light). This research may focus on spatial image consistency, individual observer differences, and ambient light adaptation. The goal is to develop computational models that can explain which aspects of display capabilities influence the perceived quality of the content.
The successful candidate will be encouraged to work with the project partner, LG Electronics, including taking part in internships.
The results of the work will be made freely available as open-source projects.
The successful candidate will start the PhD programme in October 2023.
Our group consists of PostDocs and PhD students investigating ways in which computer vision, computer graphics and signal processing can be improved by incorporating the models and knowledge of human vision. The group consistently publishes their work at premium computer graphics and vision venues, such as SIGGRAPH, CVPR, ECCV, IEEE TIP. The position is within the Graphics & Interaction Group (Rainbow) of University of Cambridge's Department of Computer Science and Technology, a vibrant and internationally leading environment. Collaboration with researchers at other universities and industries around the world is encouraged and there are strong links within the group with local, national and international companies.
We seek candidates with a strong background in Computer Science, Colour Science, and/or Image Processing (1st class honours degree or equivalent, although a Master's is particularly desirable) with a particular interest in colour, image processing and machine learning. The successful candidate must work with large quantities of data and possess excellent programming and software engineering skills.
Candidates need to meet all prerequisites for admission to the PhD in Computer Science (please refer to: https://www.cst.cam.ac.uk/admissions/phd).
This position is open to applicants from anywhere in the world; all university tuition fees will be paid by the project, and the successful candidate will receive a stipend at the UKRI rate (https://www.ukri.org/our-work/developing-people-and-skills/find-studentships-and-doctoral-training/get-a-studentship-to-fund-your-doctorate/), currently £17,668 per year.
Students wishing to pursue a PhD at the University of Cambridge are required to submit a short research proposal outlining the work they intend to carry out during the PhD. Candidates should get in touch with Dr Rafal Mantiuk to discuss this before applying, outlining their ideas for initial research directions.
The applicants are recommended to contact Dr Rafal Mantiuk (email email@example.com) before applying. Dr. Mantiuk will advise on the research proposal that needs to be submitted with the application.
Complete applications, including two academic references, research proposal, transcripts and degree certificates, CV and a cover letter, should be submitted via the Applicant Portal by 17th of February 2023, see https://www.graduate.study.cam.ac.uk/how-do-i-apply.
Please provide a Curriculum Vitae (CV) and a cover letter outlining your relevant past experience, drawing particular attention to relevant software experience and linking to one or more examples of code written (e.g. a GitHub handle). Queries regarding the application process should be directed to firstname.lastname@example.org using the reference number below.
Please quote reference NR34058 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.