Job: Call for JSPS Postdoctoral Fellows (JSPS/CNRS programme)

Thierry Hamon thierry.hamon at UNIV-PARIS13.FR
Sat Mar 17 21:41:26 UTC 2012

Date: Sat, 17 Mar 2012 11:37:40 +0100
From: Thierry Poibeau <thierry.poibeau at>
Message-Id: <8539A747-DD48-47EC-812F-046C3FA2C15E at>

Call for JSPS Postdoctoral Fellows
Development of novel algorithms for post-disaster surveillance from
massive social network data
The Japan Society for the Promotion of Science (JSPS) runs an excellent
scheme for inviting international researchers to come and work at
Japanese universities and research institutes for 12 to 24 months.  The
fellowships have offered quite generous terms that include monthly
salary, round trip air ticket, housing subsidy, settling in allowance,
accident and sickness coverage, local travel grant, and a grant in aid
for research expenses. For conditions, application deadlines and
up-to-date details please see

( are currently collaborating on a project
aiming at providing novel algorithms for post-disaster surveillance from
massive social network data. In this context, we would like to host
applicants willing to work in this area and to be based at the
Japanese-French Laboratory for Informatics (JFLI) in Tokyo for one or
two years. Note that applicants from France who apply through CNRS
should be either French nationals or French residents.
Please send expressions of interest on or before March, 31 by sending a
CV, a cover letter and one or two relevant publications to Nigel Collier
<collier at> and Thierry Poibeau <thierry.poibeau at>.
Applications are administered by CNRS with a final deadline of 16 April
2012 (see and
Recent public health disasters such as the 2010 Haiti earthquake, the
2011 Tohoku earthquake/tsunami and the Fukushima nuclear reactor leakage
have dramatically shown the human costs that societies face at times of
large-scale crisis. In a very short space of time governments must
decide on how to allocate scarce national assets to mitigate the
disaster and alleviate suffering of victims. At the same time
communities under pressure have shown great resilience and willingness
to help each other. Putting together those in need with those capable of
providing resources is a key objective in future disaster mitigation.
Traditional sensor networks on which planners rely such as general
practitioner networks and radiation monitors are expensive to maintain
and may offer insufficient coverage during times of peak
requirement. For this reason we propose to explore the use of
non-traditional sources of information to help governments, NPOs and
international agencies identify areas of need during large scale
disasters. Social media data in the form of Twitter messages have proven
useful for early warning in the case of earthquakes and epidemics. So
far though such studies have focused on a narrow set of linguistic
features without incorporating any knowledge of the underlying network
topology. Understanding the dynamics of how the network of users relate
to each other, finding hotspots and mapping these to real world
locations will form part of a new approach to disaster information
systems which our groups plan on collaboratively developing.
Twitter has been active without major disruption during the Fukushima
accident. In Tokyo, the surface lines have been down for two days but
one mobile network (out of three) has always been in working order, so
we really think this scenario is realistic. It is anyway rewarding to
monitor social media since it has been proven that the response time in
case of disaster is largely lower when compared to public authorities
Position description
We are looking for a Post-doc whose main objective will be to develop
algorithms and knowledge resources that identify communities of need and
supply through linguistic and topological analysis as well as grounding
of those communities in locations of the real world.  Needs will
correspond to anxiety about basic resources that naturally arise after
disasters such as safety, food, water, medicine, communications and so
on. These needs and their corresponding supply chains have been the
focus of manual detection in various humanitarian projects such as
Ushahidi. The difference we hope to make in this work is to analysis the
personal reports automatically using advanced algorithms. In the first
instance LaTTiCe and the Collier Lab aim to develop a collaborative
project on the topic for two years.
Skills required
- computer science, esp. a strong experience in software development
- machine learning
- natural language processing
- fluent in English
- knowledge or interest in Japanese language
- interest in blogs and new media analysis

Message diffuse par la liste Langage Naturel <LN at>
Informations, abonnement :
English version       : 
Archives                 :

La liste LN est parrainee par l'ATALA (Association pour le Traitement
Automatique des Langues)
Information et adhesion  :

More information about the Ln mailing list