瑞士洛桑联邦理工学院(EPFL)2022年招聘博士后职位（感觉运动系统建模）

瑞士洛桑联邦理工学院(EPFL)2022年招聘博士后职位（感觉运动系统建模）

洛桑联邦理工学院（École Polytechnique Fédérale de Lausanne），简称“EPFL”，又称瑞士联邦理工学院（洛桑），位于瑞士联邦洛桑，最初可以追溯到1853年建立的私立学校，后正式成立于1969年，与姊妹校苏黎世联邦理工学院一起组成瑞士联邦理工学院，是瑞士联邦经济事务、教育与研究部的一部分 。EPFL是欧洲卓越理工大学联盟战略成员，专注于工程技术、自然科学与建筑学的教育与研究。

Postdoc position to model the sensorimotor system

Ecole Polytechnique Federale de Lausanne (EPFL)

Job description

Main duties and responsibilities include : The Alexander Mathis Group of Computational Neuroscience & AI (UPAMATHIS, https: // mathisgroup.org) at EPFL (Lausanne, Switzerland) has one open postdoc position in to model the sensorimotor system funded by the Swiss National Science Foundation (SNSF). The goal is to build deep learning models of the sensorimotor system with a particular focus on proprioception based on known anatomical, pharmacological, lesion, behavioral and physiological data. We will then test predictions with our experimental collaborators. EPFL is one of the leading Institutes of Technology in Europe and offers extremely competitive salaries and research infrastructure.

Related work: DMAP: a Distributed Morphological Attention Policy for Learning to Locomote with a Changing Body Alberto Silvio Chiappa, Alessandro Marin Vargas, Alexander Mathis. NeurIPS (in press), 2022. Contrasting action and posture coding with hierarchical deep neural network models of proprioception Kai J. Sandbrink, Pranav Mamidanna, Claudio Michaelis, Matthias Bethge, Mackenzie Weygandt Mathis, Alexander Mathis, BioRxiv, 2022.

Your profile :Requirements: Candidates should have a Ph.D. and a strong publication record in computational neuroscience or related fields. An ideal candidate would have prior experience in:

Reinforcement learning

Machine learning

Modeling neural data

Biomechanics

Fluency in oral and written English is required.

Start date :Deadline and starting date: The ideal starting date is spring 2023.

Term of employment : Fixed-term (CDD)

Duration : 1 year, renewable

Remark : Only candidates who applied through EPFL website or our partner Jobup's website will be considered. Files sent by agencies without a mandate will not be taken into account.

Reference : Job Nb 2669