JOB: Postdoc in signal processing and machine learning

JOB: Postdoc in signal processing and machine learning PDF Imprimir E-mail
Miércoles, 20 de Diciembre de 2017 19:45

University of Essex (UK) - School of Computer Science and Electronic Engineering
The Essex BCI and Neural Engineering Lab is pleased to announce this postdoctoral position in the Horizon 2020 project "NEVERMIND: Neuro-behavioural predictive and personalised modelling of depressive symptoms during primary somatic diseases with ICT-enabled self-management procedures". The project started approximately 2 years ago and has 2 more years to run.
Web site: http://www.nevermindproject.eu/
The Essex team is leading the development of the real-time decision support system. Physiological data, along with sleep and speech analysis, are combined with social interaction monitoring, mood agenda and questionnaire scores to evaluate all the aspects of patients (psychological, physical, and social) as a whole with the aim of predicting the severity and onset of depressive symptoms (see for example http://bit.ly/2B5Fg17 ). The successful applicant will investigate and develop advanced signal processing and machine learning algorithms for prediction purposes. The ideal candidate will have received a PhD in Biomedical Engineering, Electronic Engineering, Computer Science or a closely related discipline, and is expected to have significant experience of biomedical signal processing and machine learning techniques. Applicants are also expected to have a strong publication record as first author, ideally including publications in 1st quartile journals in relevant areas.

Appointment will be made as Senior Research Officer.
Salary: £32,548 to £34,521 per annum
Duration: Fixed-Term until December 2019
Closes: 4th January 2018
Job Ref: REQ01062

Further information and application instructions:
http://www.jobs.ac.uk/job/BGH330
http://www.essex.ac.uk/hr-jobpacks/science_health-csee/REQ01062_Jobpack.pdf

For further information and inquiries, please contact Dr Luca Citi Esta dirección electrónica esta protegida contra spam bots. Necesita activar JavaScript para visualizarla