** Apologies for cross-postings ** Dear Colleagues,
I would be very grateful if you could forward this job advert to anybody who could be interested. The highlight is on machine learning for user interaction modelling. Here are some information for the positions. ** Application deadline 14th of August** To apply https://vacancies.essex.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VACANCY_ID=773982KP3K&WVID=9918109NEm&LANG=USA https://www.jobs.ac.uk/job/BTV423/senior-research-officer-in-social-media-modelling A PhD scholarship on the same topics is also out with deadline on the 30th of August Check <http://sites.google.com/site/dimitriognibenehomepage/jobs> http://sites.google.com/site/dimitriognibenehomepage/jobs Kind regards, Dimitri *Postdoc and Phd Positions in: Modelling beliefs dynamics of social media users with machine learning methodologies at University of Essex funded by VolkswagenStiftung (Volkswagen Foundation)* Project: Courage Applications are invited for a 4 years position of Senior Postdoctoral Research Officer and a PhD shcolarship on ht project “COURAGE: A Social Media Companion Safeguarding and Educating Students”. This project is an international collaboration funded by VolkswagenStiftung (Volkswagen Foundation) as part of the Artificial Intelligence and the Society of the Future funding initiative. The project partners include the Universitat Pompeu Fabra (Spain), the Istituto per le Tecnologie Didattiche of the National Council of Research ITD-CNR (Italy), Hochschule Ruhr West (Germany) and the Rhine-Ruhr Institute for System Innovation (Germany). The project aims to develop a Virtual Social Media Companion that educates and supports teenage school students facing the threats of social media such as discrimination and biases as well as hate speech, bullying, fake news and other toxic content. The project involves a substantial experimentation aspect in collaboration with multiple schools around Europe. It will thus provide a unique chance to perform interventions to test the validity of social interaction theories and governance methods. The Essex team will drive two strands of this work, the machine-learning-based user beliefs dynamics modelling aspect and the process of analysing visual and textual content. More specifically, we aim at developing Bayesian computational models of beliefs dynamics of social media users to support governance and educational strategies. These models will also be applied to evaluate socially relevant variables, such as trust and inclusion. We will build on and implement state-of-the-art CV, NLP & AI methods to provide measurements of sentiment, bias, hatefulness, veracity, polarization, and sensationalism of social media content. In addition, we will drive forward the state of the art in detecting hate speech and biased content. The companion will actively counteract this kind of content, balancing it with opposite perspectives and proposing specifically themed challenges adopting ideas used in games. The successful candidate will be based in the School of Computer Science and Electronic Engineering at Colchester Campus of The University of Essex. The post is available for four years with a start date from September 2019. To apply: https://vacancies.essex.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VACANCY_ID=773982KP3K&WVID=9918109NEm&LANG=USA<https://www.google.com/url?q=https%3A%2F%2Fwww.jobs.ac.uk%2Fjob%2FBSW396%2Fsenior-research-officer-in-social-media-modelling&sa=D&sntz=1&usg=AFQjCNGdFip9lUdHrfOC8Qc928R6lbgXvA> For more information: https://sites.google.com/site/dimitriognibenehomepage/jobs?authuser=0 Applicants are encouraged to contact Dr. Dimitri Ognibene<mailto:dimitri.ognib...@essex.ac.uk> (dimitri.ognib...@essex.ac.uk<mailto:dimitri.ognib...@essex.ac.uk>) for informal enquiries and further information on research objectives. -- Dimitri Ognibene, PhD Lecturer in Computer Science and Artificial Intelligence Department of Computer Science and Electronic Engineering, University of Essex, UK http://sites.google.com/site/dimitriognibenehomepage/ Skype: dimitri.ognibene
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