FindA University Ltd Featured PhD Programmes
Engineering and Physical Sciences Research Council Featured PhD Programmes
University of Sheffield Featured PhD Programmes
FindA University Ltd Featured PhD Programmes
University of Reading Featured PhD Programmes

PhD Studentship in Detection and Mitigation of Online Harms

  • Full or part time
  • Application Deadline
    Sunday, September 08, 2019
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

About This PhD Project

Project Description

Applications are invited for a full PhD Scholarship starting in January 2020 (or as soon as possible thereafter) to undertake research in the areas of social media mining, natural language processing and computational social science, with a focus on tackling online harms such as disinformation and hate speech in social media. The project aims to develop novel methods that assist with the detection of deceitful and harmful content online, especially where they can have a damaging effect on individuals or society at large, or an impact offline leading to crime. The PhD will be supervised by Dr. Arkaitz Zubiaga (http://www.zubiaga.org/).

The PhD will be based in the QMUL Cognitive Science (CogSci) Research Group (http://cogsci.eecs.qmul.ac.uk/), an interdisciplinary group with strong publication record and high international impact, which is part of the School of Electronic Engineering and Computer Science (http://www.eecs.qmul.ac.uk), Queen Mary University of London, UK.

Qualifications:

All applicants should have a first-class honour degree or equivalent, or a MSc degree, in Computer Science (or a related discipline). Applicants should have a good knowledge of English and an ability to express themselves clearly in both written and spoken form. The successful candidate must be strongly motivated to undertake doctoral studies, must have demonstrated the ability to work independently and to perform critical analysis.

Applicants are expected to possess fundamental knowledge and skills in two or more of the following aspects:
• Excellent knowledge of data science methods.
• Prior experience in social media mining and/or natural language processing.
• Excellent programming skills, ideally in Python.
• Experience with deep learning algorithms.
• Experience working with large datasets.

All nationalities are eligible to apply for this studentship. We offer a 3-year fully funded PhD studentship supported by Queen Mary University of London including student fees and a tax-free stipend starting at £16,777 per annum. In addition to the studentship, we also welcome applications from self-funded students with relevant backgrounds.

To apply, please follow the online instructions specified by the college website for research degrees: http://www.eecs.qmul.ac.uk/phd/how-to-apply/. Steps 2 onwards are applicable in this case. Please note that we request a ‘Statement of Research Interests’. Your statement (no more than 500 words) should answer two questions:
(i) Why are you interested in the topic described above?
(ii) What relevant experience do you have?

In addition to this, we would also like you to submit a sample of your written work. This might be a chapter of your final year or masters dissertation, or a published conference or journal paper.

In order to submit your online application you will need to visit the following webpage: https://www.qmul.ac.uk/postgraduate/research/subjects/computer-science.html. Please scroll down the page and click on “PhD Full-time Computer Science - Semester 2 (January Start)”. The successful PhD candidate will be a member of the CogSci research group. You should mention this in your application.

Applicants interested in the post, seeking further information or feedback on their suitability are encouraged to contact Dr. Arkaitz Zubiaga at with subject “Online Harms PhD Studentship”. All applications must be made via the website mentioned above.

The closing date for applications is 8th September, 2019.
Interviews are expected to take place in September 2019.
Starting date: January 2020 (dates can be flexible).

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.

Your enquiry has been emailed successfully





FindAPhD. Copyright 2005-2019
All rights reserved.