The AI-Wear project, funded by the French National Research Agency (ANR), aims to revolutionize the assessment and monitoring of individuals with Autism Spectrum Disorder (ASD). This ambitious project seeks to leverage the power of Artificial Intelligence (AI) to analyze electrophysiological data collected from non-invasive wearable devices. The successful candidate will be crucial in developing cutting-edge anomaly detection methods to identify stress levels from noisy and heterogeneous electrophysiological signals.
The primary responsibility of the post-doctoral researcher will be to design and evaluate novel AI-based algorithms for stress detection. This includes developing robust methods to handle the challenges posed by real-world data, such as noise and high heterogeneity across subjects and acquisition conditions. A key focus will be identifying the most informative electrophysiological signals for stress detection and translating the developed techniques into a user-friendly software tool.
The successful candidate is expected to actively contribute to the scientific community by publishing research findings in high-impact journals and presenting work at leading conferences. Furthermore, they will actively participate in team meetings and the journal club, co-supervise master's students, and contribute to managing StressID, the team's dataset for stress identification research. This is an exciting opportunity to contribute to ground-breaking research with the potential to significantly improve the lives of individuals with ASD.
About the team. This post-doctoral position will be hosted within the AI4Health@EURECOM research group led by Prof. Maria A. Zuluaga. Prof. Zuluaga currently holds an ERC Consolidator Grant, providing access to cutting-edge research infrastructure and fostering a vibrant and competitive research environment. The candidate will benefit from such a dynamic and collaborative research environment. The AI-Wear project fosters strong interdisciplinary collaborations, providing opportunities to interact with researchers from diverse backgrounds, including academic institutions (Mines St Etienne), clinical institutes (CHU Nice), and industry partners (O-Kidia). This multidisciplinary approach will enrich the research experience and facilitate the translation of research findings into real-world applications.
Requirements
- PhD degree in a relevant discipline (e.g. computer science, machine learning, physics, biomedical engineering or related fields).
- Strong theoretical and practical knowledge in applied mathematics, statistics, machine learning, time series and analysis and data science, in general
- Strong programming skills. Ideally, previous experience with Python
- Demonstrated publication track record
- Good command of English for reading/writing scientific articles and delivering oral presentations
- Previous experience with handling and manipulating healthcare data is a plus
Application
The application must include:
- Detailed curriculum vitae,
- List of publications specifying the three most important publications,
- A cover letter stating your motivation and fit for this project
- Name and address of three references.
Applications should be submitted by e-mail to secretariat@eurecom.fr with the reference: DS/MAZ/AIWEAR/012025 before March 15th 2025.
Start date: June 2025
Duration: 18-month fixed-term contract