Postdoc Positions at INRIA, Sophia Antipolis, France
Open postdoctoral positions at INRIA, Sophia Antipolis, in the broad intersection of information theory, game theory, and artificial intelligence.

The following postdoctoral appointments at INRIA, Sophia Antipolis, are for one year, but may be extended up to two years subject to a performance review. Candidates are expected to have a PhD degree in mathematics or areas related to information theory and game theory. Skills in french language are not required.

Postdoc Position 1: Data Integrity Attacks in Information Systems
The objective of this postdoc is to study data integrity attacks that capitalize on the existing vulnerabilities of machine learning techniques. The study of this problem demands addressing two important challenges. Firstly, the problem of characterizing the impact of attacking the data that is fed to the machine learning method. To this end, the problem is formulated using information measures that provide quantitative and operationally meaningful metrics for describing the relationship between the training data and the observed data. Secondly, the problem of detecting the attack can be tackled drawing from the links between information theory and statistical inference. By researching these two problems the project will shed light into the vulnerabilities of machine learning techniques and will develop novel attack detection techniques.
To Apply:
Apply before: August 15, 2021(hard deadline)

Postdoc Position 2: Information and Decision Making
The objective of this postdoc is to  characterize the interplay between data acquisition and information processing in decentralized decision making by bringing together tools from information theory and game theory. The central object of study is the influence that decision makers involved on a common decision making process can exert on each other via revealing, hiding or distorting information. This problem is central in the comprehension of problems including decentralized optimization and decentralized machine learning subject to local information constraints.
To Apply: 
Apply before: September 30, 2021

Contact: Samir M. Perlaza ([email protected])