PhD grant - "multigraph clustering and business applications"
Company/Institution name: University of Lyon 1 & EMLyon Business School
Job description: PhD grant (3.5 years) on data science of complex systems and business applications, starting in September 2017.
The candidate will be working on large networks, develop algorithms of clustering and exceptional subgroups mining to identify subnetworks of interest. Such data are both heterogeneous and structured, and can be represented as networks of information, ie attributed multigraphs.
The research work will be both fundamental and applied.
The fundamental research part consists in building new algorithms of community detection coupled with exceptional subgraphs extraction in a dynamical setting (time evolution of the network).
The applied research part consists in applying the above to real data from social media and companies networks, such as: recommandation of new relations or paths, identification of influencers, diffusion of
information, analysis of the network's time evolution...
References and more details (in French) are given in the attachement (contact us to discus this).
This is a joint PhD between the University Lyon 1 (LIRIS lab, math and computer science doctoral school), and EMLyon Business School. The candidate will share his or her time between the two institutions.
- Céline Robardet, Professor at University Lyon 1 and INSA Lyon, head of the machine learning & data mining group at the computer science lab LIRIS (https://liris.cnrs.fr/?set_language=en). Contact: firstname.lastname@example.org
- Jean Savinien, Associate Professor at EMLyon Business School, head of research of the Data R&D Institute (http://data.em-lyon.com/), and mathematician (on leave from the University of Lorraine). Contact: email@example.com
Skills expected from the candidate:
- solid graduate-level ground in computer science
- real know-how of data-science: from the big-data tech (dbms, spark, hadoop...), to the data handling and processing (eg python, pandas, sklearn...), and machine learning and statistical learning mastery.
- appetite for business applications
- confortable with graduate mathematics (knowledge of graph theory, bayesian statistics, random processes would be a plus).
Contact us with a resume, and recommandation letters from academics
(supervisors of research internship for instance)
E-mail address to apply firstname.lastname@example.org
Salary range: 30k€ per year (approx 1,500€ netto per month + a 13th month)