Postdoc in “Learning Methods for Safe-against-Uncertainty Control”

The topic mainly requires skills which often come with a PhD in statistical machine learning and/or mathematics (candidates which are going to obtain their PhD before the starting date of the position will be considered as well). 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 proposed subject shall lead to the acquisition of strong theoretical and numerical skills in learning-based modelization of control systems described by stochastic differential equations.

The offered position consists of a 18-month postdoc, funded by Dr. Riccardo BONALLI’s ANR JCJC project ROCH. The candidate will work at L2S (Laboratoire des Signaux et Syst`emes) in Gif-sur-Yvette, one of the leading laboratory in systems and control at Universit ́e 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. In the latter case, Prof. Marco PAVONE will offer supervision as an external collaborator.

The starting date coincides with the candidate’s earliest convenience starting from February 1, 2023. Salary and benefits are in accordance with the French ANR Agreement (salary indication: 3100–3300 e per month gross). A candidate’s background check, in accordance to the French HFDS, see this website (in French), is part of the recruiting process. To apply, please send the following documents to Dr. Riccardo Bonalli (email: riccardo.bonalli@centralesupelec.fr):
• curriculum vitae, motivation letter, and research statement,
• transcripts of courses with grades and obtained degrees, and list of publications,
• contact information for three academic references,
• up to 3 research-oriented documents (e.g., PhD thesis, conference/journal publication)