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Portal > Offres > Offre UMR8023-REMMON0-003 - Attracteurs quasi-continus dans les réseaux de neurones: étude de l'apprentissage et de la dynamique de diffusion (H/F)

Quasi-continuous attractors in neural networks: study of learning and diffusion dynamics (H/F)

This offer is available in the following languages:
Français - Anglais

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General information

Reference : UMR8023-REMMON0-003
Workplace : PARIS 05
Date of publication : Thursday, November 21, 2019
Type of Contract : FTC Scientist
Contract Period : 9 months
Expected date of employment : 1 January 2020
Proportion of work : Full time
Remuneration : about 2500 euros (gross salary)
Desired level of education : PhD
Experience required : Indifferent


A position for a young researcher (postdoc level) is open for studying the learning of conitnuous or quasi-continuous attractors by neural nets, as well as the dynamics of diffusion within these attractors.


Researches will consist in developing and applying analytical and numerical methods, inspired from statistical physics, for the learning of quasi-continuous attractors in neural networks. Models will then be applied to various kinds of data, including in particular data from the HFSP "Analog models for language processing" collaboration.


expertise (PhD level) in
- Statistical physics/statistical field theory
- Neural networks models

Work Context

The postdoc will work in the team "Statistical physics and inference for biological systems".

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