We are excited to announce a post-doctoral research associate position in the field of fake news detection from a theoretical computer science perspective.
The rise of fake news and misinformation is a threat to our societies. Even though we are not always able to quantify the effect of misinformation, it is clear that it is polarising the society and often leads to violence and promotes racism. Much of the fake news detection is based on human intervention that is often too slow to stop it-reliable automated fake news detection is urgently needed. In particular, it is important to develop a scalable approach that works across different languages with minimal human intervention.
The research position is a timely and exciting opportunity to help prevent the spread the fake news.
The position is fully funded for up to two years and will be supported by two to three PhD-students. The approach of the project is two-fold. In a first step, the goal is to improve our knowledge of clustering algorithms/community detection algorithms that a practically relevant. For example, one research direction would be to analyse (through proofs and simulations) practically relevant algorithms such as Louvain and Kernighan-Lin https://en.wikipedia.org/wiki/Louvain_method and https://en.wikipedia.org/wiki/Kernighan%E2%80%93Lin_algorithm). Another promising research direction is to study more realistic versions of the stochastic block model
( https://en.wikipedia.org/wiki/Stochastic_block_model) such as variants with additional edges within the communities.
The second part of the project is to develop abstract models of fake news propagation and to analyse them. There is a wide range of possibilities here and many exciting ideas are waiting to be explored. One key project in this area is an ongoing collaboration with Wikipedia (Wikimedia) with the goal of predicting which pages have to be ‘protected’ (limited editing rights). This is important since some articles are so controversial that users endlessly change details back and forth resulting in so-called “edit wars”.
You will need to be highly experienced in theoretical computer science (or mathematics), stochastic analysis, as well as have high-impact research publications in related areas and ideally programming experience. The research will have a substantial multidisciplinary ambition, but a PhD in computer science, mathematics or engineering is essential.
Our staff and students come from all over the world and the Department is proud of its friendly and inclusive culture. Diversity is positively encouraged with a number of family-friendly policies, including the operation of a core hours policy, the right to apply for flexible working and support for staff returning from periods of extended absence, for example maternity leave. The Department of Informatics is committed to ensuring an inclusive interview process and will reimburse up to £250 towards any additional care costs (for a dependent child or adult) incurred as a result of attending an interview for this position.
This post will be offered on a fixed-term contract for 2 years
This is a full-time post – 100% full time equivalent
Skills, knowledge, and experience
- PhD in computer science, artificial intelligence or related field
- Strong research record in computer science and/or artificial intelligence as
- evidenced by publications in high quality journals and conferences
- Strong experience in mathematical methods
- Enthusiasm to work collaboratively with partners from multiple disciplines