We are opening several reinforcement learning position at Inria Scool. Please, take also a look at this page. https://team.inria.fr/scool/job-offers.
Postdoc
- One 18m postdoc position about recommender systems in the context of the Pl@ntNet Inria research project. The focus is on estimation/improvement of annotation expert users by means of contextual multi-armed bandits approaches, with a unique opportunity to consider real data. Please apply here. Preferred starting date is early spring 2024.
Please contact O-A. Maillard by email with 3 of your main publications, CV, motivation letter and recommendation letter. The positions can be filled as soon as possible.
PhD
Funding available depending on applicant.
2024 internhips
Below is a list of funded internships proposals, you can contact me in case you are interested. We expect students with a solid mathematical background specifically in statistics, information theory and/or dynamical systems.
- Multi-armed bandits for soil-regeneration of agrosystems: Theory and application, with a usecase in Madagascar.
- Multi-armed bandits for patient follow-up, with a usecase at Lille Hospital.
These are intended for Master 2 or outstanding Master 1 students, and generally open the possibility to start a PhD later on. If you are interested, go ahead and contact me directly.
In case you want to apply for PhD, I strongly encourage you to read (a substantial part of) the following books and lecture notes:
Books
- Prediction Learning ang Games
Nicolo Cesa-Bianchi, and Gábor Lugosi. Cambridge University Press, 2006. - Concentration inequalities: A nonasymptotic theory of independence
Stéphane Boucheron, Gábor Lugosi, and Pascal Massart. OUP Oxford, 2013. - Self-normalized processes: Limit theory and Statistical Applications
Victor H. Peña, Tze Leung Lai, and Qi-Man Shao. Springer Science & Business Media, 2008. - Pac-Bayesian supervised classification: The thermodynamics of statistical learning
Catoni, Olivier. IMS, 2007. - Bandits algorithms
Tor Lattimore, Csaba Szepesvári. - Algorithms for Reinforcement Learning
Csaba Szepesvári. Synthesis Lectures on Artificial Intelligence and Machine Learning 4.1 (2010): 1-103. - Markov Decision Processes: Discrete Stochastic Dynamic Programming
Martin Puterman.
Lecture Notes
- Mathematics of Statistical Sequentiel Decision Making.
Odalric-ambrym Maillard (my Habilitation dissertation). - Statistical Learning Theory and Sequential Prediction
Alexander Rakhlin, Karthik Sridharan - Concentration of Measure Inequalities in Information Theory, Communications and Coding,
Raginsky, Maxim, and Igal Sason. Now Publishers Inc., 2014. - Course on Reinforcement Learning
Alessandro Lazaric.