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Research Associate in longitudinal user modelling and data mining of a large mental health social network dataset

Applications are invited for a Research Associate (Data Scientist) position on longitudinal user modelling and data mining of a large mental health social network dataset

Analyzing Social Network data for mental health research is of importance because of the inherent nature of mental health related data. With the increase of user-generated sensor data, there is a need to tailor Natural Language Processing methods to enable richer analysis capabilities for technology-based interventions.

The project will aim at mining a large Mental Health Social network dataset with focus on longitudinal user modelling, either on a personalized or on a community basis. The project will also develop methods for measuring the influence and similarities of users across different points in time.

The position will be an opportunity to conduct research on Deep Learning using neural networks within the wider context of Sentimental Analysis, Text mining and Social Network Analysis.

The post holder will also travel/work collaboratively with project partners (including academics, clinical psychiatrists & health professionals), help in organizing a few networking events and a Datathon.

We are looking to fill this position as soon as possible.

Additional information: fixed term until 31 July 2020 and full time (37 hours per week)

To Apply follow this link:


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Recipient: Prof. eiman Kanjo
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