In particular, this project has two main objectives:
- Refine existing approaches, such as boosting algorithms or neural networks, to include domain-specific knowledge, in order to improve their performances;
- Develop measures of uncertainty around their results, to allow the users estimating how much they should trust the results.
The latter, in particular, is a topic of extreme interest in all the fields in which statistical/machine learning is implemented, and goes in the direction of explainable AI.
This project is a collaboration between the Department of Mathematics and the Hylleraas Centre for Quantum Molecular Sciences, with the external participation of the University of Bonn (Germany).
- Master’s degree in statistics or a related quantitative subject with proven competence in statistics.
- Candidates with documented experience in scientific programming will be prioritized.
Call 1: Project start autumn 2021
This project is in call 1, starting autumn 2021. Read about how to apply