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Postdoctoral Research Associate in Machine Learning for Social Network Analysis

University of Oxford - Department of Engineering Science

Location: Oxford
Salary: £33,309 to £40,927 per annum, Grade 7
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 28th September 2021
Closes: 29th October 2021
Job Ref: 153423

Location: Department of Engineering Science, Parks Road, Oxford OX1 3PJ

Salary: Grade 7: £33,309 - £40,927 per annum

We are seeking a full-time Postdoctoral Research Assistant experienced in Machine Learning for Social Network Analysis to join Professor Xiaowen Dong’s and Professor Janet Pierrehumbert’s research groups in the Department of Engineering Science at the University of Oxford. This is a fixed term role until 30th September 2023 with possible extension subject to funding.

This is a research project that aims to diagnose and predict social fragmentation and the echo-chamber effects in online discussion forums, such as Reddit. You will be required to develop and implement novel graph-based machine learning and natural language processing algorithms to identify and predict social fragmentation at early stages of the online discussion. You will also write reports on your research and publish these as papers in leading conferences and journals.

You should possess a doctorate, or be near completion of a doctorate, in machine learning, signal processing or a relevant subject, together with a good publication record at major machine learning and signal processing venues, with a background in graph-based machine learning (e.g., graph neural networks, graph signal processing) and/or social network analysis.

Informal enquiries may be addressed to Prof Xiaowen Dong ( or Prof Janet Pierrehumbert (

Only applications received before midday on 29th October 2021 can be considered. You will be required to upload a covering letter/supporting statement, including a brief statement of research interests (describing how past experience and future plans fit with the advertised position), CV and the details of two referees as part of your online application.

The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology.

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