PhD Position in Computational Neuroscience of Human Motor Adaptation

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Key Words

Details of the offer

This project aims to uncover neural mechanisms of motor adaptation. The tools will include advanced machine learning, mathematical modeling (dynamical systems) on existing data and conducting experiments on healthy participants performing motor tasks with simultaneous EEG recordings.
Objectives: The student will work towards achieving the following aims:
    • Aim 1: Develop a Predictive Model of Motor Adaptation: Create an explainable machine learning pipeline capable of predicting movement in a multi-trial motor adaptation experiment involving a joystick, using already collected data (multiple datasets)
    • Aim 2: Design and Implement a Real-Time BCI System: Develop a real-time, closed-loop, passive Brain-Computer Interface (BCI) system, leveraging the ML models developed in Aim 1, to modulate task parameters and optimize motor adaptation.
    • Aim 3: Validate BCI-Enhanced Motor Adaptation: Evaluate whether the BCI system developed in Aim 2 can enhance motor adaptation by conducting an experiment with healthy participants.
Depending on the candidate’s profile, the PhD work will cover all or a subset of these aims.

Type of job

Type of contract CDD

Application deadline

Employment start date 2025-11-01

Contact

https://sdrive.cnrs.fr/s/TPwgCpG6z8rPwBR