[Closed application] PhD Position in ML Explainability – Differential Explainability

In the frame of the TRAIL joint research lab between AXA and Sorbonne University, we are pleased to open a new PhD position in machine learning explainability.
The objective will be to develop the novel idea of “differential interpretability” and propose solutions to explain the differences between two models, in particular after re-training or mechanisms like transfer learning.

The candidate should have a master’s degree in Computer Science, AI/ML, applied mathematics or equivalent, experience in research or R&D and a strong motivation.

The position is open at Sorbonne University TRAIL joint research lab.

  • Title: Defining Differential Explanations: Understanding the Dynamic of Changes in Machine Learning Models
  • PhD Proposal (PDF): TRAIL_Differential_XAI_PhD_Proposal
  • To apply: the application is closed