Computational Legal Analysis - Classifying and Understanding Remedies in Comparative Labour Law

Classifying and Understanding Remedies in Comparative Labour Law (CURE) is a 5-year comparative project, originally funded by the ERC and guaranteed by UKRI, based at the Department of Law, University of Manchester and led by Professor Aristea Koukiadaki. The project sets a new intellectual agenda and direction in comparative labour law by examining the concept and function of remedial rules and institutions. The 5-year project adopts a multi-dimensional, comparative and multi-method research design to evaluate how the juridical concept of remedies has evolved across different dimensions of the employment relationship in a set of different national systems (i.e. France, Greece, Poland, Sweden and the UK). Data collection and analysis will include legal doctrinal and empirical (i.e. legal computational and qualitative) methods.

A PhD studentship is provided to work on the computational legal analytics aspects of the project, supervised by Professor Aristea Koukiadaki and a colleague based in Computer Science at the Universuty of Manchester. The primary focus of the PhD studentship will be to establish and implement computational and analytical techniques in the areas of natural language processing (including topic modelling), computational linguistics, and machine learning corpora for latent or hidden variables underling the process of legislative and judicial decision-making on remedial rules in labour law. They will construct and analyse datasets consisting of parliamentary corpora, legal judgments, court opinions, statutes, and other relevant documents. The ideal candidate should have an interest in the relationship between technology, law and society.

The PhD student will work with the project team, consisting of five postdoctoral scholars and another PhD student. The PhD student will be expected to develop and complete a doctoral thesis on computational legal analytics with a particular focus on labour law. The successful candidate will take part in the writing up of the results of the research and in the curation and archiving of datasets constructed for and used in the project, in both cases working in conjunction with the PI and the research team. There will be opportunities for the successful candidate to present the results of their work under the project and funding to support their participation in conferences in the UK and abroad.

Eligibility criteria

Academic entry qualification

Bachelor's (Honours) degree in a cognate subject (i.e. computer science, mathematics, engineering, or a quantitative social science or digital humanities discipline) at 2:1 or above (or overseas equivalent); and Master's degree in a relevant subject - with an overall average of 65% or above, a minimum mark of 65% in your dissertation and no mark below 55% (or overseas equivalent). 

English language

International applicants must provide one of the following:

• IELTS test minimum score - 7.0 overall, 7.0 in writing, 6.5 in other sections.
• TOEFL (internet-based) test minimum score - 100 overall, 25 in all sections.
• Pearson Test of English (PTE) UKVI/SELT or PTE Academic minimum score - 76 overall, 76 in writing, 70 in other sections.
• To demonstrate you have taken an undergraduate or postgraduate degree in a majority English speaking nation within the last 5 years.
• Other tests may be considered.

 Desirable requirements:

• Experience of working as a legal engineer, knowledge engineer or legal technologist in a commercial or research environment, and familiarity with generative language models and corpus linguistics. 

Application procedure

The application deadline will be Midnight (BST) on 20/11/24. All supporting documents must be received by the deadline and sent as a zip file to [Email Address Removed], using ‘CURE Aristea Koukiadaki’ as the email subject.

 The application must include:

• An up to date academic CV, detailing your education and qualifications; employment history; publications; and any other relevant information.
• A copy of your Bachelor’s and Master’s academic transcript and degree certificate. If your Master’s degree is pending, please provide an interim transcript.
• Supporting statement of a maximum of 500 words indicating why you would like to undertake this studentship and explaining how your focus, experience, and skills link to the research outlined above.
• Example of a piece of academic writing produced by you of up to 5,000 words (you may consider submitting two shorter pieces if these deal separately with conceptual and empirical analyses). This may be an academic essay or chapter(s) from a dissertation, in which case, an abstract or introduction outlining the context/aims/research questions of the study must also be included.
• Two academic references from individuals who can assess your suitability for PhD study and specifically relate their comments to the advertised project.

If you have any questions about the project or would like to discuss this further, please contact Dr Aristea Koukiadaki ([Email Address Removed])

Formal interviews: Interviews are expected to take place during the first week in December.

Equality, diversity and inclusion is fundamental to the success of The University of Manchester and is at the heart of all of our activities. 

We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact. 

We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status. 

All appointments are made on merit. 

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