Funding

Self-funded

Project code

CMP10191026

Department

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 will:

  • use pretrained foundation models, including Large Language Models (LLMs), for data processing/augmentation (consisting of text, audio, images, and video)
  • employ artificial intelligence and machine learning techniques, including LLMs, to identify patterns within the data
  • design a framework/methodology for hypothesis testing to confirm/reject the identified patterns

Social media content is produced and consumed at increasingly younger ages, with yet unknown effects on individuals, families, and the wider society. The type of content that is being created has also been shifting from primarily text-based to image and video-based content. 

 

This PhD project will focus on the analysis of such content using the latest advances in Large Language Models (LLMs), artificial intelligence and machine learning, to extract insights from such data and identify trends over time in relation to a variety of aspects, such as the most popular topics for different age groups, characteristics of content producers and their audiences, differences between financially-incentivized content (e.g., promotion of certain products) and non-incentivized content, and the effects of consuming such content on individuals and the wider society.

 

We are particularly interested in research that utilizes the latest findings from psychology and sociology with regard to the use of social media and its effect on users, to guide the computational analysis of social media content and identity meaningful trends over time.

 

 

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  (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

A good first degree (minimum upper second class or equivalent) or a Master’s in Computer Science, Information Science, Informatics, or a related area. Other degrees with a considerable component of data analytics with computational tools, and candidates with relevant industry experience, will also be considered.

English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

 

 

Background in data analytics, machine learning, and the foundations of natural language processing, and an interest in utilizing computational tools to understand social behaviour and interactions, and complex social systems.

 

 

How to apply

We’d encourage you to contact Dr Ella Haig (ella.haig@port.ac.uk) to discuss your interest before you apply, quoting the project code.

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. 

When applying please quote project code: CMP10191026