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Portail > Offres > Offre UMR9197-ALIGIN-029 - Ingénieur d'étude en Python (H/F)

Engineer position (M/F) for python programming of neural models

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

Date Limite Candidature : mardi 7 février 2023

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General information

Reference : UMR9197-ALIGIN-029
Nombre de Postes : 1
Workplace : SACLAY
Date of publication : Tuesday, January 17, 2023
Type of Contract : FTC Technical / Administrative
Contract Period : 6 months
Expected date of employment : 1 April 2023
Proportion of work : Full time
Remuneration : between 2280 and 2722 Eur brut per month, according to experience and the salay scale of CNRS.
Desired level of education : 3-year university degree
Experience required : Indifferent

Missions

The Computational Neuroscience team of the Paris-Saclay Institute of Neuroscience (NeuroPSI) hires an engineer (“ingénieur d'étude”) position to develop computer tools (in Python) to model neuronal populations. The goal of the work is to build a computational model comprising several human brain regions, using the (python-based) tool “The Virtual Brain”. This work will contribute to the European project "Human Brain Project" (HBP).

Activities

- Develop and optimize open-source software to simulate neural systems
- Construct networks of neural populations in python
- Collaborate with local and international partners of HBP

Skills

- Programming in Python language (C++ would be a plus)
- Produce efficient and clear code, tested and documented
- Mastering of technical English
- Knowledge in neuroscience
You must be autonomous and also able to work in a team.

Work Context

The Computational Neuroscience team comprises about 12 researchers, students and engineers, and is part of the Department of Integrative and Computational Neuroscience in the Paris-Saclay Institute of Neuroscience (NeuroPSI). The team is interdisciplinary, at the interface between neuroscience, physics, engineering, computer science, and with a strong implication in European projects.

Constraints and risks

None

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