Dear Colleagues,
Our team is offering various PhD proposals, whose topics concern
Uncertainties and imprecision in Spatial Interpolations for Urban Risk Mapping: the PhD student would integrate the HOUSES national project, that aims at handling severe uncertainties in geostatistics, notably to assess pollutants levels in water and grounds.
Robustness in Explainable AI: the PhD student would join our junior professor chair and develop robust explanation methods for AI predictive models, as well as explanation methods for uncertain predictions.
Robust event detection: the PhD student would join the SAFE AI chaire and develop statistical learning method that would detect events with pre-specified statistical guarantees, notably by working on how to obtain calibrated predictions for such tasks. The first retained case studies would concern obstacle detection for aid-decision in partially or fully automated vehicles, a domain on which our laboratory has significant expertise.
For each of these, we seek highly motivated students having a strong background in mathematics or computer science, with a focus on a topic connected to the PhD proposals (e.g., statistics, machine learning, …)
Potentially interested candidates can find more details on the page https://www.hds.utc.fr/~sdesterc/dokuwiki/.
Best regards
Sébastien
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Sebastien Destercke, Ph. D. CNRS researcher in computer science.