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Research Assistant/Associate in Automatic Analysis of Facial Expressions and Affect (Fixed Term)


Research Assistant £26,243 - £30,395 or Research Associate £32,236 - £39,609

Fixed-term: The funds for this post are available for 2 years in the first instance.

A position is available to work on a project related to digital transformation in health and care with a starting date of 1 February 2019 (or the earliest thereafter). The aspect of the project the applicant will work on relates to facial expression and facial action unit recognition and analysis of user affective state on mobile devices in real time. This will be achieved by devising novel spatio-temporal models for vision-based analysis and interpretation of facial input data with a consideration for mobile system effectiveness and efficiency.

Essential requirements: Candidates should have a degree in computer science(or close to completion), electronic engineering, mathematics or a closely related discipline, with experience and interest in Affective Computing, Computer Vision and Machine Learning. In particular, they should have technical experience working with facial data for Facial Analysis and/or Facial Expression Recognition. Candidates must demonstrate very good programming skills and be self-motivated. Appointment at research associate level requires a strong publication record.

Desirable skills: It is desirable that the candidate has expertise in programming real-time computer vision applications.

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) and a strong publication record. 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.

This position is funded through a European Union (EU) Horizon 2020 Grant. Applicants should contact Dr Hatice Gunes (http://www.cl.cam.ac.uk/~hg410/) 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 NR17002 on your application and in any correspondence about this vacancy.

The University values diversity and is committed to equality of opportunity.

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Apply online