[Infovis] Post-­doctoral position in Visual Analytics at the University of Montpellier 2, France

Arnaud Sallaberry arnaud.sallaberry at lirmm.fr
Fri Apr 25 15:35:36 CEST 2014

Visual Analytics for heterogeneous text streams.

LIRMM Lab (http://www.lirmm.fr/lirmm_eng/contact-­‐us), Montpellier 
(http://en.wikipedia.org/wiki/Montpellier), France

Dr. Arnaud Sallaberry at LIRMM (http://www.lirmm.fr/~sallaberry/) and 
Dr. Mathieu Roche at CIRAD (http://www.lirmm.fr/~mroche).

The heterogeneity of data is an important issue in Big Data area. Data 
is not only large in volume and produced at a high speed (velocity), but 
also holds many kinds of input (technical heterogeneity), structures 
(data model heterogeneity) and meanings (semantic heterogeneity). We 
would like to recruit a postdoctoral researcher for one year to address 
this specific issue from a visual analytics approach.

A lot of documents (web pages, scientific publications, reports, and so 
forth) contain much useful information. Mining heterogeneous data, 
according to their structure and to their content becomes a major issue 
in data mining area. A key problem consists of sharing these various 
data and/or information and integrating them in order to discover new 
knowledge. In addition, microbloggings contain crucial information to 
take into account in a global system that mines heterogeneous data. For 
instance, people participating in on-­line forums, microblogging or 
discussing on social networks leave behind them digital traces of 
information on a variety of topics.
The analysis of individual messages and their aggregation represent a 
considerable challenge for currently existing methods, as user-­written 
texts present a special type of stream setting. In this project we plan 
to investigate the epidemiology issue of farmed animals in collaboration 
with UMR Cirad-­INRA CMAEE. The aim is to detect weak signals concerning 
the beginning of epidemics (e.g., African swine fever, foot and mouth 
disease, bluetongue, avian influenza).

Visual exploration of textual data is an active area of research. Most 
of the methods proposed deal with static texts like discourses, books 
or, more generally, string data. Most of these methods require 
well-­formatted data and are not adapted to streams and/or heterogeneous 
The candidate will be in charge of discovering efficient text mining 
techniques for extracting structured data, and designing visual 
interfaces to interact with these structures and explore the data. 
He/She will process following the steps of the Munzner’s nested model 
for visualization design.

-­ A PhD degree in Computer Science on the domain of Information 
Visualization or Visual Analytics with interest in Text Mining.
-­ An excellent publication record, including papers in high­‐impact 
journals and conference proceedings.
-­ Strong experience in programming languages.
-­ Knowledge of visualization libraries (e.g. D3, GraphViz, ...) is an 
­‐ Must be proficient in English.

The project will be formally jointly supervised by Dr. Arnaud Sallaberry 
at LIRMM (http://www.lirmm.fr/~sallaberry/) and Dr. Mathieu Roche at 
CIRAD (http://www.lirmm.fr/~mroche).

Starting date:
September/October 2014 (some flexibility is possible)

Conditions of employment:
Net salary: ~ 2200 euros / month
Interested candidates are requested to send an application by e-‐mail to 
Dr. Arnaud Sallaberry, arnaud.sallaberry at lirmm.fr and Dr. Mathieu Roche, 
mathieu.roche at cirad.fr with the subject field: 'LABEX: Post-­‐Doc 
visualization position'.
The application should consist of a motivation letter and a curriculum 
vitae with a list of publications and description of any previous 
research you have held. Furthermore, names and contact information for 
three references are required.
Applications will be reviewed immediately and the review process will 
continue until the position is filled.


Arnaud Sallaberry

Associate Professor - Maitre de Conferences
LIRMM, Universite Paul Valery Montpellier 3

LIRMM - UMR 5506 - CC 477
161, rue Ada
34095 Montpellier Cedex 5

Tel. : +33 (0)4 67 41 86 53

E-mail : arnaud.sallaberry at lirmm.fr
Home Page : http://www2.lirmm.fr/~sallaberry/

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