Annonce en lien avec l’Action/le Réseau : aucun

Laboratoire/Entreprise : UMR CNRS LRMS @ Rouen
Durée : 14 mois
Contact : faicel.chamroukhi@unicaen.fr
Date limite de publication : 2018-12-31

Contexte :
This research will be performed in the framework of the project Asterics: Statistical learning for large-scale unsupervised data representation and classification

Sujet :
The candidate will participate to the creation of a data science platform dedicated to unsupervised
classification of high-dimensional data. The first step concerns prototyping developed algorithms by the
members of the project AStERiCs https://asterics.lmno.cnrs.fr, their integration into this platform on various
real applications. These are unsupervised classification algorithms based on latent variable models. The
second step is to integrate the algorithms that will be developed during the project. A part of the work will be
carried out in collaboration with the LMNO lab on distributed regularized mixture models with
environmental applications / genomic sequences.
The main missions are:
(i) Developing unsupervised learning models
(ii) Prototyping unsupervised learning algorithms
(iii) High performance distributed cloud computing
(iv) Web integration and interfacing with the platform.

Profil du candidat :
• Required Profile :
◦ PhD in statistics/statistical leaning or computer science with specialization in machine learning
◦ Experience in latent data models and complex data analysis
◦ Experience in software development
◦ Skills in working on real-world data and applications
◦ Programming skills in Matlab/R/Python
◦ Skills on big-data platforms (Hadoop/Spark, MapReduce), Cloud computing, OLAP, web technologies

Formation et compétences requises :
PhD in statistics/statistical leaning or computer science with specialization in machine learning

Adresse d’emploi :
Laboratoire de Mathématiques Nicolas Oresme, Université de Rouen, Normandie

Document attaché : AStERiCs-PostDocIGR-LMRS.pdf