Réseaux team

Difference between revisions of "Job opportunities"

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=== PhD Positions ===
 
=== PhD Positions ===
* '''[[File:TS-cybersec-iiot.pdf|Cybersecurity for industrial networks]]''', under the supervision of Fabrice Theoleyre (CNRS), Thomas Gaberan (Technology & Strategy)
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* '''[[Media:TS-cybersec-iiot.pdf|Cybersecurity for industrial networks]]''', under the supervision of Fabrice Theoleyre (CNRS), Thomas Gaberan (Technology & Strategy)
  
 
* '''[https://orange.jobs/jobs/offer.do?joid=111927&lang=EN AI-Powered Reliable and Available Wireless Mesh Networks for the Factory of the Future]''', under the supervision of Fabrice Theoleyre (CNRS), Quentin Lampin and Marion Dumay (Orange Labs).
 
* '''[https://orange.jobs/jobs/offer.do?joid=111927&lang=EN AI-Powered Reliable and Available Wireless Mesh Networks for the Factory of the Future]''', under the supervision of Fabrice Theoleyre (CNRS), Quentin Lampin and Marion Dumay (Orange Labs).

Revision as of 09:09, 17 May 2022



Permanent positions

  • CNRS researcher: we strongly suggest the applicants to contact very early the research group to discuss their research statement (Deadline for the proposal: January)
  • Associate Professor: we strongly encourage the applicants to contact the research group to prepare their application package

PhD Positions

  • Anomaly detection in the Internet of things, under the supervision of Julien Montavont, Thomas Noël and Cristel Pelsser.

Communicating objects are now omnipresent on the Internet forming what is called the Internet of Things. Unfortunately, the popularity of the Internet of Things makes it a favorite target for cyber criminals. With more than thirty years of experience in Internet protocols, the scientific community has proposed many solutions for detecting attacks or abnormal behavior. Due to their characteristics, the objects have required the specification and deployment of new communication protocols. Many flaws are still present and require a precise analysis of the traffic to identify and correct them. The purpose of this thesis is to deal with anomaly detection in the Internet of Things. Initially, we need to characterize the traffic coming from these networks to extract global rules which make it possible to identify abnormal behavior. The application of these rules will allow us to correct flaws in the protocols involved, or to deploy countermeasures to make the Internet of Things more secure. We also want to offer “honeypot” solutions to gather real attack traces potentially carried out by AI.

Postdoc

  • all the positions have been filled this year.

Internships

  • all the positions have been filled this year.