Research Assistant £26.243 - £30,395 or Research Associate £32,236 - £39,609
Fixed-term: The funds for this post are available for up to 18 months.
We are looking for a highly motivated postdoctoral research associate with an interest in colour and human visual perception. The project will combine methods from psychophysics and vision science with modern machine learning to develop new models of human vision, which will enable intelligent display algorithms, adaptable to visual perception.
The successful candidate will be responsible for experiment design, data analysis, modelling, and work with prototype high dynamic range displays. She/he will spend a month-long secondment in the Psychological Science department of the University of Liverpool to facilitate cross-disciplinary training and joint work on the project.
The research associate will have the opportunity to work on real-life applications, such as the adjustment of image appearance depending on the user's visual performance (age-adaptive rendering).
This project presents a unique training opportunity for the research associate who will benefit from experts working on the same topic (colour appearance) but come from different theoretical backgrounds (Rafal Mantiuk, Computer Graphics/Vision - University of Cambridge; Sophie Wuerger, Human vision - University of Liverpool). The project will be advised by Graham Finlayson (University of East Anglia), Jasna Martinovic (Aberdeen) and Garrett Johnson (Apple Inc.).
This project will investigate human perception in the context of novel high dynamic range display technologies. It involves psychophysical experiments as well as modelling spatio-chromatic appearance under a wide range of light levels, from mesopic light levels to the levels produced by high-dynamic range displays (0.01 to 15000 nit). It will devise and validate a new model of spatial colour vision that will support detailed analysis and prediction of how content on new displays will be perceived. Such a model can then be used to automatically process images so that their appearance is preserved when presented in a significantly different manner: at different brightness levels (display dimming), at different contrast (tone-mapping, ambient light compensation), under different viewing conditions (dark cinema vs. bright living room). The model will also be able to take into account potential individual differences in observer sensitivity and implement the effect of age-related changes in the visual system.
The model will be tested in novel applications, such as adjustment of image appearance depending on the user's visual performance (age-adaptive rendering), and adjustment for display brightness, contrast and ambient illumination (display-adaptive rendering).
Essential Skills: Candidates should have a degree in computer science, electronic engineering, psychology (colour vision) or a closely related discipline, with experience and interest in colour and human vision. The position requires very good programming skills.
Desirable Skills: It is desirable that a candidate has expertise in one or more of the following areas: machine learning, Bayesian inference, statistical methods for psychophysics, high dynamic range imaging.
This position can be filled by an appropriate candidate at research assistant or research associate level, depending on relevant qualifications and experience. Appointment at research associate level is dependent of having a PhD (or equivalent experience). Where a PhD has yet to be awarded appointment will initially be made as a research assistant and amended to research associate when the PhD is awarded.
Applicants should contact Dr Rafal Mantiuk (http://www.cl.cam.ac.uk/~rkm38/) for further information.
To apply online for this vacancy, please click on the 'Apply' button below. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.
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; 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 ORCID profile. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.
Please quote reference NR17198 on your application and in any correspondence about this vacancy.
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