University of Portsmouth
ZZ004028 - Research Associate in Multi-modal Data Analysis
Faculty of Technology
School of Computing
Research Associate in Multi-modal Data Analysis
Employment type: Fixed term (1 year)
Employment basis: Full time
Salary: £29,301 to £32,958
Post number: ZZ004028
Closing date: 29 August 2017
Interview date: 08 September 2017
The objective of this research project, funded by EU FP7 Framework, is to deliver the next generation robot-enhanced therapy (RET), which will be able to infer the ASD children’s psychological disposition and assess their behaviour in order to select therapeutic actions. It will also develop clinical interactive capacities for social robots. Multi-sensory data will be used to provide quantitative support for the diagnosis and care of ASD.
Candidates must have a Master/PhD in a relevant discipline. Solid knowledge of multiple sensory data processing and motion recognition is required. The successful candidate will need to write reports, research papers and presentations. You will also need to assist documenting software. You will be a part of research team and work closely with our external EU partners to make sure the project progresses well.
For this post you will have:
- Master/PhD in Robotics or related discipline.
- Strong software development and real-time programing skills.
- Experience in multi-modal data sensing and analysis.
- Good Publications in related Journals and conferences.
For any inquiries, please contact Dr Zhaojie Ju via email at firstname.lastname@example.org.
Applications (application form, CV, publication list and research statement) should be submitted via the online application system.
The Intelligent Systems and Biomedical Robotics group in School of Computing is a leading research group in computational intelligence and application with an emphasis on approximate computation; it has published over 300 international refereed books, journals and conference papers including three Best Paper Awards and one Competition Prize. Currently it has two academic members, one technician, four postdoctoral research associates and six PhD students. The research has been strongly supported by EPSRC, EU FP7, DTI, the Royal Society, JSPS and local industrial partners.
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