|Funding for:||UK Students, EU Students|
|Funding amount:||£15,609 - please see advert|
|Placed On:||22nd May 2022|
|Closes:||10th August 2022|
This project will develop an open-set misinformation classification model, which addresses several challenges in misinformation. The proposed model will be designed under an open-set (i.e. infinite number of misinformation categories) assumption, which provides robust category classification performance with continuously evolving misinformation categories. The model will also provide new category detection functionality with prediction explanation to help fact-checkers and relevant professionals discover shifts in misinformation topics. The project will also investigate few-shot learning approaches to allow fast model adaptation in response to misinformation category evolution.
You will carry out research on the latest advances in computational methods for analysing onlinebmisinformation, and more specifically, investigate multilingual deep learning methods. Within the studentship, there is expectation to disseminate via national and international conferences and journals.
In this studentship, you will work in the well-connected, world-leading Natural Language Processing (NLP) research group at the University of Sheffield, which has a reputation for internationally leading research and is one of the largest such groups in Europe.
A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent) or an MEng/MSc (or equivalent, or near completion) with first-class honours or distinction in Computer Science, or a closely related area. If your first language is not English and you have not studied in an English-speaking country, you will have to provide an English language qualification.
Closing date: Successful applicants will be expected to start in October 2022. Please submit your application latest by 10th August 2022 for Home Students and 10th April 2022 for International Students. Later applications may be considered depending on the funds remaining in place
For any general queries, please contact Dr. Xingyi Song, e-mail: email@example.com
The award funds tuition fees and a tax-free stipend at the UKRI rate (currently £15,609 per annum) for up to 3.5 years
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