PhD position: NLP for crisis management

Job offer posted on 6 July 2022

DesCartes Program (Work Package 5) is looking for a PhD in NLP for crisis management, as part of the DesCartes program, which aims to develop disruptive hybrid AI to serve the smart city and to enable optimized decision-making in complex situations, encountered for critical urban systems.


The DesCartes programme is developing a hybrid AI, combining Learning, Knowledge and Reasoning, which has good properties (need for less resources and data, security, robustness, fairness, respect for privacy, ethics), and demonstrated on industrial applications of the smart city (digital energy, monitoring of structures, air traffic control).

The program brings together 80 permanent researchers (half from France, half from Singapore), with the support of large industrial groups (Thales SG, EDF SG, ESI group, CETIM Matcor, ARIA etc.).

The research will take place mainly in Singapore, at the premises of CNRS@CREATE, with a competitive salary and generous funding for missions.

Read more about the DesCartes program here.


Recently, social media has been widely used to generate valuable information in crisis situations (ecological crises, sanitary crises, etc.), showing that traditional means of communication between population and rescue departments (e.g., phone calls) are clearly suboptimal (Olteanu et al.,2015). One of the main characteristics of messages posted during crisis events is that both urgent and non urgent messages are drowned in a deluge of off-topic or personal messages that may contain crisis-related keywords. New tools are thus needed to early access useful information that will allow the emergency units to anticipate actions, providing therefore actionable information that will help to set priorities for the human teams and decide appropriate rescue action (Spiliopoulou et al. 2020, McCreadie et al, 2019;Imran et al., 2015,Kozlowski et al, 2020,Bourgon et al, 2022).

The thesis takes place within the Descartes project, a large France-Singapore collaboration project on applying AI to urban systems. The project will make use of Natural language processing (NLP) models to analyse and extract users’ intentions, making detection of user future
actions and the AI conversation systems more intelligence and practical. We target intentions for urban crisis management and study in particular: (1) text classification in extremely imbalanced datasets, (2) transfer learning strategies to handle different types of crisis with a particular focus on zero-shot and few-shot learning approaches,, and finally (3) Analysis of data in real-time.


Preferred :

– Master degree in Computer science with solid background in NLP and/or machine learning
– A good experience in deep learning approaches for NLP
– Good programming skills in Python


N. Bourgon, F. Benamara, A. Mari, V. Moriceau, G. Chevalier, and L. Leygue. Are Sudden Crises Making me Collapse? Measuring Transfer Learning Performances on Urgency Detection. In Proceedings of the 19th International Conference on Information Systems for Crisis Response and
Management (Work in progress paper), 2022

D. Kozlowski, F. Saudemont, F. Benamara, A. Mari, V. Moriceau, and A. Boumadane. A Three-level Classification of French Tweets in Ecological Crisis. Information Processing & Management, 57(5), 2020

Olteanu, A., Vieweg, S., and Castillo, C. (2015). What to Expect When the Unexpected Happens: Social Media Communications Across Crises. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, CSCW ’15, pages 994–1009

McCreadie, R., Buntain, C., and Soboroff, I. (2019). TREC incident streams: Finding actionable information on social media. In Zeno Franco, et al., editors, Proceedings of the 16th International Conference on Information Systems for Crisis Response and Management, Valencia, Spain, May 19-22, 2019. ISCRAM Association.

M. Imran, C. Castillo, F. Diaz, S. Vieweg, Processing Social Media Messages in Mass Emergency: A Survey, ACM Computing Surveys 47 (2015) 67:1–67:38.

Spiliopoulou E, Maza S.M, Hovy E, Hauptmann A. Event-Related Bias Removal for Real-time Disaster Events. Findings at EMNLP 2020


The thesis will happen within the France-Singapore collaboration, with advisors from both sides. The student will be registered at the University of Toulouse, and part of the IRIT lab, but is expected to spend a good part of the thesis in Singapore at the A*star Institute for Infocomm Research (I2R), with funding provided by the Descartes program.
The thesis will be supervised on the French side by Farah Benamara (IRIT) and co-advised by Jian Su from the Astar lab. The French advisor will also spend time at Astar during the thesis.

Additional information:

– Duration of the position: 36 months
– Starting date: October 2022


Workplace Address: CREATE Tower (NUS Campus), 1 Create Way #08-01 Singapore 138602

Please send a short cover letter describing your suitability for the position, detailed CV with academic ranking (if any) and publication list, a concise description of research interests and future plans, and academic transcripts to:

– Jian Su 

– Farah Benamara 

We will begin reviewing applications for the positions immediately.