Skills Applicants must prove their motivation for teaching and have a high‐level scientific record in accordance with UGA’s ambitions and standard and be in alignment with UGA’s values in particular openness to the world, probity, integrity and ethics, capacities for team work, interest to invest for the community and a sense for environmental and social engagement.
The recruited person will show a particular interest for the Grenoble research environment with a focus on the mentioned laboratories and the MIAI AI institute https://miai.univ‐grenoble‐alpes.fr/. It is expected that the recruited person will develop interactions and collaborations with the members of the institute.
Research profile AI methods produce results that are expected to directly impact decisions or predictions about people in multiple sensitive areas such as justice, healthcare, finance, autonomous driving, and defense. Two important research directions, which can be combined, emerge: on one hand, ensuring that AI is reliable (whether by a priori methods or runtime monitoring), and, on the other hand, making its workings explainable.
With respect to reliability, the goal is to develop solutions incorporating rigorous approaches, based on formal, as well as data engineering and model engineering methods, so as to obtain guarantees regarding reliability (safety and transparency), efficiency (volume of data, data quality, energy consumption of model inference…) and robustness (with respect to realistic perturbations).
Also, explainability, transparency, and ability to generalise AI models are significant issues for the trust‐ based acceptability of AI systems, be they based on machine learning algorithms or algorithms for diagnosis, recommendation, voting, assignment, or collective decision. The goal here is to render understandable the elements taken into account by the AI system when it produces results.
In this context, the LIG, Verimag and GIPSA laboratories would like to recruit a junior professor to develop reliable and/or explainable AI methods. The research profile and research statement of the candidates shall focus on topics relevant to explainable and reliable AI, for instance in one of the following emerging research areas:
- Approximation (whether local or global) of black‐box models by interpretable models,
- Computation of the importance of attributes for decision‐making or prediction or selection of variables,
- Learning of interpretable characteristics,
- Visual or textual explanations, speech,
- Causal models,
- Abstraction and generalization
This research project will be supported by a €200k funding from ANR and it may be co‐funded from UGA.
Teaching profile The recruited person will deliver 96 hours of tutorials (or the equivalent) per year during the tenure-track process, which amounts to a half teaching load.
They will take part in the teaching carried out by MIAI (3IA) and the AMI CMA and in particular those of MOSIG, and international master’s program common between IM2AG and ENSIMAG.
Scientific outreach, open science The scientific dissemination will mainly take the form of publications and international conferences. Dissemination may also take the form of valorization of research results within the framework of industrial partnerships or start‐up development.
The project is part of an open science approach to both research results and data thanks to the GRICAD UAR (research unit) and the funding of our GATES project funded by the national ExcellencES program.
Information for candidates The chair is awarded for 3 to 6 years depending on the laureate’s profile. At the time of tenure, the laureate will need to hold the Habilitation à Diriger des Recherches (Habilitation to Conduct Research) qualification.
Université Grenoble Alpes recruits on the basis of skills and makes use of all talents. It encourages candidates with disabilities to apply for teaching and research positions.
Teacher‐researchers are required to reside at the place where they perform their duties (Art. 5 of Decree No. 84‐431 of June 6, 1984).
Application https://www.galaxie.enseignementsup...
You may inquire about the research aspects of the position at VERIMAG by e-mailing: verimag-direction@univ-grenoble-alpes.fr
