Machine Learning for the Detection and Probabilistic Quantification of Morphological Traits in Bioindication (diatoms, foraminifera)

Job alert: a 36-months PhD position on AI applied to image-based aquatic biomonitoring, to be started in October 2025

Objectives: image processing pipelines for species classification and morphological trait quantification, uncertainty estimation methods to quantify the confidence of model predictions, interactive and weakly supervised learning strategies to minimize the need for human-labeled data

Expected skills: solid grounding in machine learning, particularly deep learning, mathematics and computer science. Interest or even a specialisation in ecology.

Supervision: Pr Cédric Pradalier (GeorgiaTech Europe) and Dr Jérémy Fix (CentraleSupélec Metz, LORIA), in collaboration with Dr Martin Laviale (Univ. Lorraine, LIEC)

Funding: BIOINDIC-IA project (ANR)

For more details and application (until June 30th): https://adum.fr/as/ed/voirproposition.pl?site=adumR&matricule_prop=65683#version