진학프로석·박사 채용 접수 플랫폼

Objective

This postdoctoral project will take an innovative multidisciplinary approach by developing Big Data/AI based techniques to create, query and analyse argumentation models based on textual resources.

Context

Techniques and methods to be developed belong to the following Big Data /AI areas of current computer science research:

• • modelling and capturing of opinions using Big Data, Machine Learning and Artificial Intelligence methods,
• • learning from online data sources (e.g., online discussions, relevant texts, etc.)
• • information diffusion, opinion dynamics and social networks.

Research Objectives

Modelling and capturing opinions and their evolution is useful for diverse applications. This work will combine text analytical functions with (semantic) argumentation models so as to be able to provide at the end an argumentation graph. The (semantic) argumentation graph will be able to capture the interactions around a subject and their characterizations (classification of arguments) as in favour or against, their temporal characteristics (what preceded what) and the actors involved so as to allow advanced reasoning and analysis.

Argumentation models is a rather new area of semantic description and analysis of the (online and offline) exchanges of different actors and can help to understand the trajectory and the diffusion and evolution process of ideas that reach the public in forms and contents different than the ones they started with. We would like to combine this with ML/AI tools to help in the construction of the argumentation graph and other ML/AI tools to allow its subsequent analysis.

We will work with specific use cases analysing public discussions on important issues of today like the climate change, environment and debates around medical issues like epidemics and vaccinations.

Requirements

• • The applicant should have successfully defended a PhD in computer science, big data, machine learning, data science or related field. Applicants that will defend their PhDs before or around the beginning of the period are also welcome to apply.
• • The applicant should demonstrate ability and experience in developing applications to execute applied computer science projects. Experience in tools used for big data analytics (in R, Python, Java or all) is a plus (additionally if applied in a cloud environment). 
• • Language: the working language will be English

Location

ETIS Lab in Cergy-Pontoise (suburb of Paris France)

Institutional Context

The funding for this research is provided by the UNKNOWNPATH project funded by the CY Initiative of Excellence. We expect the successful applicant to play an important role in the overall project development and the associated research. The postdoc will be affiliated and located in the ETIS lab at the CY Cergy Paris University and will work under the supervision of Professor Dimitris Kotzinos (ETIS / CYU) and collaborate with the other researchers in the project.

Tentative Starting Date: 

As soon as possible.

Application

If interested, please send your application (including a detailed CV, university transcripts, a copy of the PhD thesis and/or scientific papers if available, as well as a list of personal references and a motivation letter) in PDF format to Professor Dimitris Kotzinos ([email protected]) with title “Postdoc UNKNOWNPATH”. Further informal enquiries are also welcome.

Applications will be welcome until the position is filled, those submitted before 30/08/2026 will be considered in priority.