PhD Student

Job description

Ph.D. research on Artificial Intelligence for the evaluation of financially distressed companies to assist judges in Commercial Courts

CONTEXT

• Fundamental and applied research will be performed at Ghent University under the supervision of prof. Joke Baeck (Faculty of Law and Criminology), prof. Klaas Mulier (Faculty of Economics and Business Administration) and prof. Thomas Demeester (Faculty of Engineering and Architecture).
• The proposed research fits within the FWO-funded research project “Evaluation of distressed enterprises using explainable machine learning: construction of an artificial intelligence algorithm to assist judges in Belgian Enterprise Courts”.
• The activities of the PhD are embedded in a stimulating interdisciplinary environment, with the focus on contributions on the use of AI by courts and/or the use of AI (machine learning) for corporate bankruptcy prediction.
• The PhD candidate will thus work on the intersection between AI & Law / Bankruptcy Law, Data Science and Corporate Finance. Depending on the candidate’s preference, emphasis can be placed either on the legal aspect (within the Private Law department), the economic aspect (within the Corporate Finance research group), or on the computer science part (within the Internet and Data Science research group).
  
  

JOB DESCRIPTION

• In close collaboration with the supervisors as well as another PhD student, the PhD candidate will contribute to in the above-mentioned FWO-funded research project, by conducting research of the use of AI by courts and/or the use of AI for predicting corporate distress and potential bankruptcy.
• The candidate will contribute to pilot projects on the use of AI by Belgian (Commercial) Courts.
• The candidate will present research results at major international conferences and publish in international peer reviewed journals, as part of meeting the requirements for the PhD.
  
  

Job profile

YOUR PROFILE

• We are looking for a highly creative and motivated PhD student with the following qualifications and skills:
• You have (or will obtain this academic year) a master degree in Law, Computer Science, Business Engineering, Informatics or Engineering (or equivalent), with excellent qualifications at bachelor and master level.
• You are strongly interested in AI & Law (or Bankruptcy Law), Computer science (and machine learning in particular) as well as in economics and corporate finance, and have strong skills in at least one of these areas. You are eager to advance the state-of-the-art in these areas.
• You are a team player and have strong communication skills.
• You are fluent in English, both speaking and writing. Knowledge of Dutch is considered an asset but not strictly required.
  
  
  

OUR OFFER

• We offer a full-time position as a Ph.D. fellow, for an initial period of 1 year, which can be renewed up to maximum 4 years upon positive evaluations.
• We offer a dynamic and international work environment with a competitive salary and ample training and self-development opportunities.
• Envisaged starting date: flexible, but sooner rather than later (at the earliest 1 January 2024, at the latest 1 October 2024).
  
  

How to apply

INTERESTED?

We are looking forward to hear from you! Please apply by e-mail to Prof. Joke Baeck at joke.baeck@ugent.be before 1 December 2023.

Your application should include the following documents (merged in one pdf-file):

• Motivation letter (maximum one page)
• CV
• Diploma and transcript of records (bachelor and master)
  
  

MORE INFORMATION

For more information about this vacancy please contact Prof. Joke Baeck at joke.baeck@ugent.be (if your main interest is the legal aspect of the project), Prof. Thomas Demeester at thomas.demeester@ugent.be (if your main interest is in the computer science part of the project) or Prof. Klaas Mulier at klaas.mulier@ugent.be (if your main interest is in the economic aspect of the project).

Ghent University seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments.