Postdoc position in convex optimization for multiagent systems (Paris, France)

Job Description

The aim is to address the minimization of a sum of convex possibly non-differentiable functions. Typical applications of interest include generalized-lasso problems or distributed optimization in multi-agent networks. The objective is to develop and analyze new proximal optimization algorithms in a stochastic approximation framework. A special emphasis will be put Ｏn the analysis of the convergence rates of the methods.

Candidates : Ph.D in applied mathematics. Strong background in probability and/or optimization.