Postdoc offer in “Learning Methods for Safe-against-Uncertainty Control”, at L2S, Université Paris-Saclay.
One and a half year postdoc position to design learning models which offer rigorous guarantees of reliability for efficient and safe-against-uncertainty control and deployment of autonomous systems in complex settings.
Successful candidates have (or are going to obtain) a PhD in statistical machine learning and/or mathematics (major in, e.g., optimization, probability/statistics, systems and control). Expertise in the topics related to control and stochastic differential equations, as well as coding skills in Julia, Matlab, or Python will constitute valuable perks.
The candidate will work at L2S (Laboratoire des Signaux et Systèmes) in Gif-sur-Yvette, one of the leading laboratory in systems and control at Université Paris-Saclay. (S)he will be jointly supervised by Dr. Brandon AMOS (New York), Dr. Riccardo BONALLI (L2S, Gif-sur-Yvette), and Dr. Alessandro RUDI (SIERRA, Paris). In addition, a visiting period in Prof. Marco PAVONE’s laboratory at Stanford University can be envisioned to flight test the algorithms on realistic free-flyers.
More information about the position and the application process may be found in the official call: https://rbonalli.github.io/SujetPostdoc1ANR.pdf
