Research Associate in Artificial Intelligence and Software Engineering

As the successful candidate, you will primarily contribute to a partnership project with BGL – BNP Paribas, one of the major banks in Luxembourg. The title of the project is “AI for AI” and it concerns the design of an AI ‘metamodel’ tool that will monitor and improve AI algorithms effectiveness and robustness, allowing their application to business-critical use cases at scale. The objective of this project is to develop automated means to continuously monitor the performance of AI models (including NLP models) developed by BGL BNP Paribas and to determine when and how to retrain these models in order to improve their performance. Achieving these objectives requires addressing crucial research challenges such as the definition of proper quality metrics across the bank’s use cases, the identification and explaination of the limitations and blanks spots of the models, and the design of sustainable improvement mechanisms. Overall, the project supports BGL BNP Paribas in scaling-up their AI and data science activities through ground-breaking research, thereby enabling the widespread dissemination of AI products and services throughout the bank. The project is held in close collaboration with BGL-BNP Paribas and, as the successful candidate, you will be expected to program prototype tools showcasing the practical benefits of your research outcomes.

The supervision team you will be working with is:

• Maxime Cordy: research scientist at SeRVal
• Jacques Klein: chief scientist at TruX
• Tegawendé Bissyandé: chief scientist at TruX

You will be required to perform the following tasks:

• Carrying out research in the predefined areas
• Survey the scientific literature in the relevant research domains
• Disseminating results through scientific publications
• Communicate with stakeholders to collect requirements and report results
• Implement proof-of-concept software tools
• Contribute to the supervision of younger researchers (PhD students)
• Contribute to the acquisition of competitive research fundings