Project code



School of Computing

Start dates

October, February and April

Application deadline

Applications accepted all year round

Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.

The PhD will be based in the School of Computing and will be supervised by Dr Ella Haig and Dr Alaa Mohasseb.

The work on this project could involve:

  • Processing textual data
  • Using machine learning and natural language processing to extract relevant information
  • Develop automatic detection models for aspects of interest using machine learning

Misinformation and disinformation are the acts of spreading incorrect or misleading information to influence the discussion around a topic (with or without malicious intent). In recent years, such activity has considerably increased on social media, especially around political events such as elections. Moreover, previous research has shown that behind some of this activity are state-sponsored actors.

This project aims to develop automatic methods for investigating such activity from social media text using machine learning and Natural Language Processing (NLP). The data you will work with is from Twitter and includes accounts that Twitter identified as potentially belonging to state-sponsored actors.
Dr Ella Haig has over 15 years of research experience in modelling user behaviours/characteristics using artificial intelligence and machine learning techniques. Dr Alaa Mohasseb has research experience in the fields of Text Mining, Natural Language Processing, and Machine learning.

This project will give you the opportunity to work on a cutting-edge research project and gaining skills in a high-demand area (cyber-security), which would benefit your employability prospects.

Fees and funding

Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK and EU students only).

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

Entry requirements

You'll need a good first degree from an internationally recognised university or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications.  English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

The following skills and expertise are mandatory:

  • Fundamentals of data analytics and machine learning
  • Good technical skills (e.g. python, R)
  • Familiarity with machine learning toolkits (e.g. Scikit-Learn, TensorFlow).

The following skills and expertise are desirable:

  • Familiarity with natural language processing and text mining
  • Familiarity with text processing toolkits (e.g. NLTK, spaCy)

How to apply

When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process. 

October start

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February start

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