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Portail > Offres > Offre UMR7271-VIVROS-040 - Chercheur en "Cognitive Cloud" : un framework Cloud-Edge basé sur l'IA (H/F)

Researcher in Cognitive Cloud: Artificial Intelligence-enabled cloud-edge networking (H/F)

This offer is available in the following languages:
- Français-- Anglais

Date Limite Candidature : mardi 27 juin 2023

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Informations générales

Intitulé de l'offre : Researcher in Cognitive Cloud: Artificial Intelligence-enabled cloud-edge networking (H/F)
Référence : UMR7271-VIVROS-040
Nombre de Postes : 1
Lieu de travail : VALBONNE
Date de publication : mercredi 17 mai 2023
Type de contrat : CDD Scientifique
Durée du contrat : 12 mois
Date d'embauche prévue : 15 septembre 2023
Quotité de travail : Temps complet
Rémunération : Between 2833.40 and 3257.06 € gross monthly depending on experience
Niveau d'études souhaité : Niveau 8 - (Doctorat)
Expérience souhaitée : 1 à 4 années
Section(s) CN : Information sciences: bases of information technology, calculations, algorithms, representations, uses


Realization of original scientific work compatible with a post-doctoral level.
Nowadays, cloud IP traffic has become the most part of Internet traffic. A traffic that complexifies with an increasing devices diversity and traffic dynamicity. The combination of Machine Learning (ML) and Artificial Intelligence (AI) with Network Softwarization (SDN/NFV). has been proposed in the so-called Knowledge Defined Networking (KDN) to give rise to a “Cognitive Cloud:” an AI-enabled Cloud-Edge framework. This “Cognitive Cloud” will allow automatically adapting to the growing complexity and variability of Internet traffic by (i) (re)learning Cloud-Edge network control policies from data; and (ii) applying these control policies onto a (re)configurable Cloud-Edge network.

In many cases, the management of this (re)configurable Cloud-Edge network constitutes a challenging stochastic control problem, that can be modelled as Markov Decision Process (MDP) and solved under the Reinforcement Learning (RL) framework (a form of Machine Learning). Novel RL approaches could allow us to find more efficient management decisions (i.e., the control policy) to operate this Cloud-Edge network.

Then, in this postdoc, we aim to apply ML (as RL, but not uniquely) framework to the management of Cloud-Edge networks.

You can find more information on this postdoc subject on the site: https://www.i3s.unice.fr/~raparicio/project/artic/postdoc.pdf


Activities (not exhaustive list):
. Carrying out bibliographic studies in the context of the research subject of the postdoc
. Design of machine learning algorithms for networks.
. Development of software tools for carrying out the tests of algorithms mentioned above.
. Analysis and synthesis of the results of these tests (e.g. in the form of reports and presentations).
. Preparation of detailed technical documents on the scientific studies carried out.
. Publication of the main results of these studies in high-level international newspapers and conferences.
. Participation in seminars and other activities of public dissemination of the results of these studies.
. Realization of national and international missions within the framework of collaborative research projects related to the subject of the postdoc, in particular in the context of the ARTIC project, funded by the ANR, such as visits to partner laboratories.
. Co-supervise research internships and student projects in line with the subject of the postdoc.
. And, in general, participation in research activities related to the subject of the postdoc, such as collaborative research projects.


Regulatory diploma required less than two years old
. PhD degree or equivalent (ISCED level 8 according to UNESCO) in computer science / mathematics / telecommunications less than two years old, with solid experience in machine learning (artificial neural networks) and computer and telecommunication networks

- Theoretical knowledge :
. Machine learning and data science (namely neural network theory)
. Classical optimization theory (convex optimization, combinatorial optimization)
. Computer network control plane (algorithms and protocols)

- IT skills:
. Python 3.5 language
. Python frameworks (like PyCharm, Jupiter Notebook, Spyder, Conda)
. Deep Learning Libraries (like TensorFlow, Keras)
. Other IT skills such as:
. Thorough knowledge of networks and system (Unix, typically)

- Language skills:
. Scientific English is fundamental
. Scientific French is desirable, but not absolutely necessary.

- Transversal skills
. Resilience and persistence to face failure (short term).
. Taste for exploring and trying new approaches.
. Organizational skills to properly carry out personal tasks independently.
. Know how to plan and meet deadlines.
. Work in a team, especially in cross-functional mode and in an international environment.
. Love communicating (presenting) the activities accomplished.

Contexte de travail

This postdoc is part of the ANR ARTIC project (ARTificial Intelligence-based Cloud network control, cf. http://www.i3s.unice.fr/~raparicio/project/artic/), of which Ramon APARICIO PARDO is the principal investigator. This project will provide the candidate with the funds and resources necessary for their activities (participation in scientific events, equipment, computer, access to computing platforms, etc.)
The postdoc will take place in the I3S laboratory, a joint public research laboratory resulting from the collaboration of the CNRS, Univ. Cote d´Azur and INRIA. The I3S laboratory is one of the most important research laboratories in information and communication sciences in the French Riviera and was one of the first to settle in the science and technology park of Sophia Antipolis. It brings together just under 300 people.
The postdoc will work with experts in optimization, machine learning and telecommunications networks from the I3S and INRIA.

Le poste se situe dans un secteur relevant de la protection du potentiel scientifique et technique (PPST), et nécessite donc, conformément à la réglementation, que votre arrivée soit autorisée par l'autorité compétente du MESR.

Contraintes et risques


Informations complémentaires

Application file:
- Curriculum vitae, with list of publications
- Cover letter
- PhD diploma
- PhD dissertation
- Thesis (pre-)defense reports (if available)
- At least two letters of recommendation and a list of three references to contact.