Research Assistant/Associate (Fixed Term)
Cambridge Service Alliance
Date: 2 weeks ago
City: Cambridge
Contract type: Full time

Fixed-term: The funds for this post are available for 24 months in the first instance.
We are excited to announce an exceptional opportunity to advance the field of 3D video content evaluation and immersive experiences. Be at the forefront of developing groundbreaking metrics and visual models to predict quality and comfort in next-generation 3D, AR, and VR displays.
As part of our research group creators of leading perceptual metrics such as HDR-VDP, FovVideoVDP, and ColorVideoVDP you'll focus on automated solutions that detect and quantify visual artifacts, depth errors, and overall 3D content quality. Your work can be instrumental in shaping how immersive media is experienced by millions.
What You'll Do
Design and run innovative psychophysical experiments using state-of-the-art stereoscopic and VR equipment
Collect, scale, and analyse subjective data from users
Develop new visual models and predictive algorithms, combining expertise in psychophysics and machine learning
Collaborate closely with our global industry partner, Meta Reality Labs, ensuring your research has immediate, real-world impact
Why join us?
Thrive in a friendly, highly collaborative, and intellectually vibrant environment
Work with world leaders in perceptual metrics
Enjoy flexible work arrangements and access to advanced AR/VR technologies
Create research that has the potential to impact pioneering products and global standards
If you are passionate about creating the future of 3D content and immersive technology, we want to hear from you!
Essential requirements: Candidates should hold (or be close to obtaining) a PhD degree in computer science, electronic engineering, or a closely related discipline, with experience and interest in image and video quality. The candidate must have sound foundations in machine learning and image processing. It is also essential that the candidate has sufficient experience with deep learning frameworks, such as PyTorch. Excellent programming skills are required.
Desirable skills: In addition to the essential requirements, an ideal candidate should have experience working with 3D stereoscopic displays and content, have a track record of work on image or video quality, and have knowledge of psychophysical methods and visual modelling.
This position can be filled by an appropriate candidate at a research assistant or research associate 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 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 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.
This position is advertised together with another position that is at a Research Assistant level NR47142 https://www.cam.ac.uk/jobs/term/Department-of-Computer-Science-and-Technology . If you also want to be considered for that position, submit an application for both (the applications could be identical).
Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.
Applicants should contact Dr Rafal Mantiuk (http://www.cl.cam.ac.uk/~rkm38/, [email protected]) for further information.
Please quote reference NR47139 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. Please note that we provide the support of applying for the relevant visa (if required) and we reimburse the cost of the first visa.
Apply online
We are excited to announce an exceptional opportunity to advance the field of 3D video content evaluation and immersive experiences. Be at the forefront of developing groundbreaking metrics and visual models to predict quality and comfort in next-generation 3D, AR, and VR displays.
As part of our research group creators of leading perceptual metrics such as HDR-VDP, FovVideoVDP, and ColorVideoVDP you'll focus on automated solutions that detect and quantify visual artifacts, depth errors, and overall 3D content quality. Your work can be instrumental in shaping how immersive media is experienced by millions.
What You'll Do
Design and run innovative psychophysical experiments using state-of-the-art stereoscopic and VR equipment
Collect, scale, and analyse subjective data from users
Develop new visual models and predictive algorithms, combining expertise in psychophysics and machine learning
Collaborate closely with our global industry partner, Meta Reality Labs, ensuring your research has immediate, real-world impact
Why join us?
Thrive in a friendly, highly collaborative, and intellectually vibrant environment
Work with world leaders in perceptual metrics
Enjoy flexible work arrangements and access to advanced AR/VR technologies
Create research that has the potential to impact pioneering products and global standards
If you are passionate about creating the future of 3D content and immersive technology, we want to hear from you!
Essential requirements: Candidates should hold (or be close to obtaining) a PhD degree in computer science, electronic engineering, or a closely related discipline, with experience and interest in image and video quality. The candidate must have sound foundations in machine learning and image processing. It is also essential that the candidate has sufficient experience with deep learning frameworks, such as PyTorch. Excellent programming skills are required.
Desirable skills: In addition to the essential requirements, an ideal candidate should have experience working with 3D stereoscopic displays and content, have a track record of work on image or video quality, and have knowledge of psychophysical methods and visual modelling.
This position can be filled by an appropriate candidate at a research assistant or research associate 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 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 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.
This position is advertised together with another position that is at a Research Assistant level NR47142 https://www.cam.ac.uk/jobs/term/Department-of-Computer-Science-and-Technology . If you also want to be considered for that position, submit an application for both (the applications could be identical).
Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.
Applicants should contact Dr Rafal Mantiuk (http://www.cl.cam.ac.uk/~rkm38/, [email protected]) for further information.
Please quote reference NR47139 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. Please note that we provide the support of applying for the relevant visa (if required) and we reimburse the cost of the first visa.
Apply online
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