Research Assistant £26,715 - £30,942 or Research Associate £32,816 - £40,322
Fixed-term: The funds for this post are available until 31 January 2022.
A position is available to work on an exciting multi-disciplinary project related to digital transformation in health and care with a starting date of 1 May 2020 (or the earliest thereof). The aspect of the project the applicant will mainly work on relates to facial expression/ action unit recognition and analysis of user affective states in real time. This will be achieved by devising novel deep learning-based methodologies for interpretation of facial input data, and integration of the developed methodologies to the overall project pipeline in collaboration with the other project partners.
Essential requirements: Candidates should have (or be close to completing) a PhD degree in computer science, electronic engineering, mathematics or a closely related discipline, with experience and interest in Computer Vision, Machine Learning and/or Affective Computing. In particular they should have technical experience with recent deep learning methods, ideally applied to facial analysis. Candidates must have very good programming skills, be open to collaborations and be self-motivated. Appointment at research associate level requires a good (and relevant) publication record.
Desirable skills: It is desirable that the candidate (i) has experience in programming real-time computer vision applications; and/or (ii) has experience with facial analysis and/or facial expression recognition.
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 on having a PhD (or equivalent experience). Where a PhD has yet to be awarded the 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.
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Please ensure you upload your curriculum vitae; a statement of the particular contribution you make to the project based on your past and current experience and expertise (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 your Google Scholar 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 NR22818 on your application and in any correspondence about this vacancy.
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