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Research Associate on 'FakeNewsRank: A Ranking for Detecting Fake News on the Web'

University of Oxford - Department of Computer Science

Location: Oxford
Salary: £32,236 to £39,609 p.a.
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 17th April 2019
Closes: 1st June 2019
Job Ref: 140450

Department of Computer Science, Parks Road, Oxford 

Grade 7: £32,236 - £39,609 p.a. 

The Department of Computer Science has a new vacancy for a Research Associate on “FakeNewsRank: A Ranking for Detecting Fake News on the Web”. Reporting to Professor Thomas Lukasiewicz, you will have responsibility for carrying out research towards new approaches to detecting fake news on the Web, including collaborating with others, and providing guidance to junior members of the group, such as PhD students, MSc students and/or project volunteers. 

The main goals of the project are (i) to create a proof-of-concept demonstrator for computing a fake news score, denoted Fake-NewsRank, for facts, articles, authors, and websites, which measures their likelihood of being fake, and (ii) to identify any still existing key gaps or challenges. The project will also produce (iii) datasets (for two different domains, e.g., politics and the economy) of sample blog messages and news articles, containing true and fake facts, along with their authors and web addresses, and (iv) background knowledge graphs underlying these datasets. 

You will hold a PhD/DPhil (or be close to completion) in computer science, mathematics, statistics, engineering,  computational linguistics, or related discipline, together with relevant experience, and possess a good (theoretical and programming) background in machine learning, and knowledge representation and reasoning (desirably in deep learning and neural networks, deep-learning-based representations, knowledge bases and graphs, ontology languages, natural language processing, and explainable and interpretable artificial intelligence), and good software engineering skills (especially in system implementations and experimental evaluations). 

The closing date for applications is 12.00 noon on 1 May 2019.

Our staff and students come from all over the world and we proudly promote a friendly and inclusive culture. Diversity is positively encouraged, through diversity groups and champions, for example, as well as a number of family-friendly policies, such as the right to apply for flexible working and support for staff returning from periods of extended absence, for example maternity leave. 

Closing Date: 01-MAY-2019 12:00

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