University of Luxembourg

Doctoral candidate (PhD student) in SME Credit risk platform development

University of Luxembourg,

Luxembourg, Luxembourg

The University of Luxembourg is a multilingual, international research University.

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from highly motivated PhD candidates in the general area of software engineering within its SEDAN research group. SnT carries out interdisciplinary research in secure, reliable and trustworthy ICT systems and services, often in collaboration with industrial, governmental or international partners. For further information, you may refer to

The SEDAN (SErvices and Data mANagement) research group, headed by Prof. Radu State addresses impact-oriented research activities in the areas of security, service management and monitoring. More specifically the group is interested on designing architectures, algorithms and approaches in the context of the new challenges given by ever increasing volumes of data, multiple and permanent connectivity and new distributed consensus systems based on blockchain paradigms.

Doctoral candidate (PhD student) in SME Credit risk platform development

Your Role

This is a fully funded position for 3 years (extendable to an additional 4th year) connected to a partnership with Yoba, a Luxembourgish startup in the fintech business ( Therefore, the objectives of the PhD project are defined in accordance to the project directions, and also aligned with the research interest of Yoba towards their product development.

The project aims to develop models and methodologies to build a platform to assess the credit risk of small and medium sized enterprises (SMEs) using data analytics, thus allowing Yoba to make credit decisions quicker and more efficiently and thus increasing the overall availability of credit to the underserved SME sector in Luxembourg and other European markets where Yoba will operate. The technology behind this platform will be fully supported by data and machine learning models will be utilised to: i) extract information from unstructured data, ii) provide credit scoring, iii) make model drift analysis, and iv) make anomaly detection. Significant effort will be put on privacy aspects and explainable models.

The successful candidate will be supervised by Dr. Mats Brorsson (also Professor at KTH Royal Institute of technology) from the University of Luxembourg and with an industrial supervisor from Yoba, and join a strong and motivated research team lead by Prof. Radu State. The candidate is also expected to spend 20-30% of her/his time at the Yoba premises in central Luxembourg.

The position holder will be required to perform the following tasks:

  • Contribute to the project “SCRiPT – SME Credit Risk Platform”
  • Carry out research in the predefined areas
  • Disseminate results through scientific publications
  • Present results in well-known international conferences and workshops

Your Profile

Qualification: The candidate should possess a Master degree or equivalent in Computer Science, Applied mathematics, or equivalent.

Experience: The ideal candidate needs to demonstrate knowledge and skills in one or more of the following topics:

  • Machine learning
  • Natural language processing
  • Model-driven engineering
  • Data analytics

The candidate must possess strong analytical and programming skills.

Knowledge in banking, fintech, credit risk assessment is not essential but is considered an asset.

We are looking for someone who is curiosity driven and who wants to constantly learn new things.

Language Skills: Fluent written and verbal communication skills in English are required.

We offer

The University offers a Ph.D. study program with an initial contract of 36 months, with a further possible 1-year extension if required. The University offers highly competitive salaries and is an equal opportunity employer. You will work in an exciting international environment and will have the opportunity to participate in the development of a newly created university.

Further Information

Application should include:

  • Full CV, including: - For each degree received or currently enrolled in, provide the degree, institution name, institution city and country, and date (or expected date) of graduation. Include the title and short summary of your final (Bachelor / Master) Thesis if you did one. - List of publications (if any) - Name, affiliation and contact details of three referees
  • Transcript of all modules and results from university-level courses taken
  • Cover letter with motivations and topics of particular interest to the candidate (approx. 1 page)

All qualified individuals are encouraged to apply.

Deadline for applications: July 31, 2020.

For further information, please contact us at or

Please apply ONLINE formally through the HR system. Applications by email will not be considered.

Early submission is encouraged; applications will be processed upon arrival.

Ref: RCREQ0004268

Please apply via recruiter’s website.