Modeling temporal, rhythmic and social synchronization with spike neural networks
9 Février 2023
Catégorie : Doctorant
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Dans le cadre du projet ANR ModPuls (Modeling temporal, rhythmic and social synchronization with spike neural networks), nous proposons une offre de thèse dans l'UMR Euromov DHM (Ales/Montpellier).
La thèse peut éventuellement être précédée d'un stage PFE.
N’hésitez pas à vous mettre en mode pulse, et à me contacter pour toute question complémentaire.
Merci et à bientôt,
A 3-year fully funded PhD scholarship is proposed by the PhD school (ED I2S) in Alès / Montpellier within the ANR MODPULS project.
The successful applicant will become part of a dynamic research environment within the newly multidisciplinary joint research center EuroMov Digital Health in Motion.
See this offer on the EuroMov DHM website:
Start date: October 1st, 2023 (to September 2027).
Net remuneration around 1630€ monthly (including social security and health benefits).
A 6-month internship is also possible on the same project (March to August 2023). See this offer on the EuroMov DHM website:
The temporality of information is crucial to our understanding of the world. Synchronization between different events guides our perception and our actions in many tasks. For example, speech understanding is improved by lip-reading in a context of synchronization between visual and sound perception.
In the field of artificial intelligence, spike neural networks offer a paradigm inspired by the functioning of the human brain, which is based on the synchronization between neuronal impulses. These neural networks are likely to be more efficient than the classical neural networks used in the field of machine learning, and less costly in terms of hardware. They also offer new possibilities for processing temporal data and analyzing synchronizations.
The MODPULS project aims at studying the possibilities and the limits of the use of spike neural networks for the analysis of temporal data related to synchronization, rhythm, and human movement. Through a set of temporal and rhythmic data of different natures and complexities, combining audio, video and human motion data, you will have to implements synchronization tasks with spike neural networks. The fine analysis of synchronization mechanisms opens the field to numerous applications, notably in the human sciences with musical practice, but also in the medical field through the therapeutic analysis of social synchronizations.
As a PhD student, you will be responsible for:
- Independently carrying out research and completing a PhD dissertation within three years,
- Identifying or creating a dataset of temporal and rhythmic,
- Developing algorithms and methods to analyze data with spike neural networks, Recruiting participants and organize experiments in our labs,
- Reporting the results in international peer-reviewed scientific journals and conferences.
Applicants should have (or anticipate having) a MSc and research background related to computer science, audio/signal processing, or computational movement science. Knowledge in music (theoretical and practical) will be valued. French is not mandatory, but the candidate must be willing to learn French during their PhD and they must be able to communicate in English.
Applications should include a cover letter discussing your interest in the position, detailed CV, academic results (evaluation, average and ranking of the candidate during the initial course and Msc) and two reference letters. Deadline is June 18, 2023. Interviews will be conducted thereafter.
For any question or for your application, please contact email@example.com