Design and definition of Natural Language Processing models in the legal domain [Self-Funded Students Only]

   Cardiff School of Computer Science & Informatics

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  Dr Federico Liberatore, Dr Jose Camacho Collados  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Aims: The objective of this project is to apply Natural Language Processing (NLP) methods to devise and implement data-oriented applications in the legal domain. Also, the PhD project will be devoted to the extension of the state of the art with the design and definition of models specifically tailored to the object domain. This research will be hosted in the Natural Language Processing research group with connections to Spanish public institutions such as the Council of State. As such, the models will be designed and tested on real-world datasets.

Methods: This project draws from the disciplines of Natural Language Processing (NLP) and Machine Learning (ML). In broad strokes, the project will be structured as follows. i) Analysis of the context and problem to solve. ii) Literature review for the identification of improvement opportunities with regards to the problem addressed. iii) Definition of models that solve the problem and expand on the literature. In this regard, the project is focused on (but not limited to) NLP methodologies, classical ML models, neural and deep models, and mathematical programming models. iv) Development and validation of the solution methodology.

Deliverables: The results of the project will be mostly published as journal papers or as conference papers when appropriate. Dissemination will be carried out at national/international top-tier conferences through talks or posters. Successful models will be implemented and developed into working software to be used by practitioners and public institutions, such as the Spanish Council of State.

Keywords: Natural Language Processing, Machine Learning, Deep Learning, Artificial Intelligence, Legal Domain.

Contact for information on the project: Dr Federico Liberatore:

Academic criteria: A 2:1 Honours master's degree in computing or a related subject. Degrees in AI (Artificial Intelligence), Machine Learning, NLP or Data Science preferred.

Applicants with appropriate professional experience are also considered. Degree-level mathematics, computer science (or equivalent) required.

Law degree with provable knowledge of the data science domain could also be accepted.

Applicants for whom English is not their first language must demonstrate proficiency by obtaining an IELTS score of at least 6.5 overall, with a minimum of 6.0 in each skills component.

Applicants with knowledge of the Spanish language will be given preference.

How to apply:

Please contact the supervisors of the project prior to submitting your application to discuss and develop an individual research proposal that builds on the information provided in this advert. Once you have developed the proposal with support from the supervisors, please submit your application following the instructions provided below

This project is accepting applications all year round, for self-funded candidates via 

In order to be considered candidates must submit the following information: 

  • Supporting statement 
  • CV 
  • In the ‘Research Proposal’ section of the application enter the name of the project you are applying to and upload your Individual research proposal, as mentioned above in BOLD
  • Qualification certificates and Transcripts
  • Proof of Funding. For example, a letter of intent from your sponsor or confirmation of self-funded status (In the funding field of your application, insert Self-Funded)
  • References x 2 
  • Proof of English language (if applicable)

Interview - If the application meets the entrance requirements, you will be invited to an interview.  

If you have any additional questions or need more information, please contact:  

Computer Science (8)

Funding Notes

This project is offered for self-funded students only, or those with their own sponsorship or scholarship award.


Quijano-Sánchez, L., Liberatore, F., Camacho-Collados, J., & Camacho-Collados, M. (2018). Applying automatic text-based detection of deceptive language to police reports: Extracting behavioural patterns from a multi-step classification model to understand how we lie to the police. Knowledge-Based Systems, 149, 155-168.
Zhong, H., Xiao, C., Tu, C., Zhang, T., Liu, Z., & Sun, M. (2020). How does NLP benefit legal system: A summary of legal artificial intelligence. arXiv preprint arXiv:2004.12158.

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