Research positions
Postdoctoral Position
ERC project "Socsemics"
We are opening several postdoctoral researcher positions to join CNRS and Centre Marc Bloch, its interdisciplinary research lab based in Berlin, Germany. This work takes place in the context of the ERC Consolidator project “SOCSEMICS” (“Socio-Semantic Bubbles of Internet Communities”, see socsemics.huma-num.fr), led by Camille Roth and funded by the European Research Council from 2018 until 2023.
Doctoral Fellowships
ERC project "Socsemics"
We are opening at least one doctoral fellowship (3 years) to join CNRS and Centre Marc Bloch, its interdisciplinary research lab based in Berlin, Germany. This work takes place in the context of the ERC Consolidator project “SOCSEMICS” (“Socio-Semantic Bubbles of Internet Communities”, see socsemics.huma-num.fr), led by Camille Roth and funded by the European Research Council from 2018 until 2023.
Research internships
User confinement in online communities (SNA and info-viz)
Algodiv project
We open up to two internships under the joint supervision of Camille Roth and Jérémie Poiroux. For the first internship, applicants should ideally be achieving a master’s degree in computer science and related fields (e.g., applied mathematics); prior knowledge of network theory and/or online data collection is desirable. The second internship targets students in information visualization and information design.
Algorithmic guidance on cultural good consumption (online/offline)
Algodiv project
We open one internship under the joint supervision of Camille Roth and Jérémie Poiroux. Applicants should ideally be achieving a master’s degree in computer science and related fields (e.g., applied mathematics); modeling and/or online data collection skills are desirable.
Automatic Hypothesis Generation for Network Growth Models
ERC project "Socsemics"
We open up to two internships. Candidates should be achieving a Masters Degree in Computer Science and related fields. Beyond a sufficient knowledge in Computer Science, desirable skills include in particular : algorithmic complexity and graph theory, network science, machine learning (especially evolutionary computation / genetic programming), as well as python and its common scientific libraries. Ability to innovate autonomously is expected.