Post-Doctoral Researcher in Machine Learning
- Alès, Gard
- CDI
- Temps-plein
- Evaluation of variations in the results produced by XAI methods in specific study contexts (for example, image classification tasks and XAI techniques based on local interpretability using attribution methods).
- Assessing the impact of XAI methods on human-machine collaboration in simplified decision-making contexts:
- Study contexts (e.g. games, image classification) and test protocols to be taken into account.
- The selection and implementation of predictive models and XAI techniques.
- Setting up the tools needed to carry out the experiments covered by the study protocols, for example the development of simple games and decision-making interfaces.
- The implementation of the above-mentioned protocols on cohorts of human operators.
- Assessing and promoting the results obtained.
- Deep learning models, and their implementation via PyTorch (ability to train and refine pre-trained models on specific datasets on dedicated GPU computing resources), evaluation of trained models according to standard protocols.
- XAI techniques; knowledge of the main XAI methods (e.g. local and attribution methods) and tools in the field. Skills can be improved during the assignment, but knowledge of these aspects is desirable.
- An important part of the assignment is the evaluation of human-machine collaborations, i.e. assessing the impact of AI and XIA models on human decision-making; initial experience of working with human cohorts would be a plus.
- Doctorate in Computer Science on a topic related to machine learning or deep learning
EURAXESS