Post-Doctoral Research Visit F/M Postdoctoral position in web security, privacy, and online tracking

Assignment
The modern web is undergoing a massive shift with the rise of AI and the evolution of browsers and operating systems. As third-party cookies were being phased out between 2020 and 2025, the ad ecosystem evolved and launched sophisticated and opaque tracking techniques (e.g., server-side tracking, identity graphs...). Simultaneously, the development of AI and LLM is having a tremendous impact on the web by modifying its structure to better suit web agents while also integrating AI tools directly inside users' browsers. These rapid shifts and changes introduce new privacy attack vectors and security challenges and demand adequate analysis to better protect users. The postdoctoral student will help investigate this subject as part of the PEPR Cybersecurity REV project.
Main activities
We are seeking a highly motivated postdoctoral researcher to explore the boundaries of web privacy and security. The candidate will contribute to one or more of the following areas:
Analysis and measurements of advanced online tracking techniques (e.g., SST, identity graphs, first-party cookies, user ID detection)
Analyzing the security and privacy implications of AI-integrated browsing (e.g., prompt injection in browser agents, data leakage via LLM side-channels).
Understanding the shift to AI-first web (e.g., perform measurements on how the web evolves to accomodate AI tools).
Design of defensive mechanisms to better protecter users against a rising number of threats.
Skills
Qualifications

• PhD in Computer Science (Security, Privacy, or Web Systems).
• Good track record of publications in top-tier venues (A or A* conferences strongly recommended).
• Technical Proficiency: Great understanding of the Web stack (JS engines, HTTP, browser APIs). Experience with crawling tools (Playwright, Puppeteer) and data analysis is optional but very strongly recommended.
• Communication: Fluency in English (French is not required).