Senior Research Officer Social Interaction - University of Essex

Vacancy Reference Number

REQ02121

Closing Date

2 Jan 2019

Salary

£33,199 to £35,211 per annum

Address

School of Computer Science and Electronic Engineering, University of Essex

Department and project consortium

The School of Computer Science and Electronic Engineering, the Department of Psychology, and the Essex Brain-Computer Interfaces and Neural Engineering Lab are pleased to announce this postdoctoral position in the Horizon 2020 project "POTION: Promoting social interaction through emotional body odours". The project will start in January 2019 and includes partners from the Universities of Pisa (Italy), Padova (Italy), and Essex (UK), the Universitat Politecnica De Valencia (Spain), the Katholieke Universiteit Leuven (Belgium), and the Karolinska Institutet (Sweden), and three companies ISPA CRL (Portugal), SRA Instruments (France) and Feel-Ing s.r.l. (Italy). POTION proposes a novel technological paradigm to delve deeper into understanding meaningful social interaction, combining new knowledge about the chemical composition of human social chemosignals together with a novel olfactory-based technology designed to drive social behaviour.

Duties of the Role
The Essex team's work on the project focuses on the development of Bayesian (DCM and Active Inference) computational models of multimodal social interaction. This models will be applied to evaluate socially relevant variables, such as trust, presence and inclusion as well as generate optimal stimuli in artificially mediated social interactions. In particular, the models will cover the role of human chemosignals perception in social interactions. The models will be identified using neurophysiological data (e.g. EEG), peripheral physiological activation (i.e., ECG, RESP, EDA) and behavioural changes (i.e., f-EMG) collected using VR scenarios of increasing complexity.

The successful applicant will research and develop Bayesian (DCM and Active Inference) computational models of multimodal social interaction and in particular on the role of human chemosignals perception in social interactions. They will also develop robust algorithms for signal processing, statistical inference and extraction of information from EEG and other physiological signals, design and implement software for the execution of experiments with VR stimulation, and contribute to the reporting and dissemination of the project.

Skills and qualifications required
Applicants are expected to hold a PhD in Computational Neuroscience, Brain-computer Interfaces, Neural Engineering, Psychology, Machine Learning, Statistics, Physics, Mathematics, Computer Science or a closely related discipline, or equivalent professional experience or practice or be close to completion of PhD. The ideal candidate will have significant experience in computational modelling of social interaction, signal processing, statistical modelling of neural signals and processes, brain-computer interfaces, and virtual reality interfaces. Applicants are also expected to have a strong publication record (relative to their career stage) as first author, ideally including publications in 1st quartile journals in relevant areas.

We strongly encourage women to apply as they are currently under-represented in the School of Computer Science and Electronic Engineering.

At the University of Essex internationalism is central to who we are and what we do. We are committed to being a cosmopolitan, internationally-oriented university that is welcoming to staff and students from all countries and a university where you can find the world in one place.

Please use the ‘Apply’ button to read further information about this role including the full job description and person specification which outlines the full duties, skills, qualifications and experience needed for this role. You will also find details of how to make your application here.

Our website http://www.essex.ac.uk contains more information about the University of Essex. If you have a disability and would like information in a different format, please telephone (01206) 876559.

For more information and to apply, click here

Contact Details

(01206) 876559.