Researcher in Electrophysiology and Computational Modeling (M/F)

CNRS - National Center for Scientific Research; France; On-site; EUR 32,000 - 48,000; Full time

Job summary

The CNRS - National Center for Scientific Research through the Institut des Neurosciences Paris-Saclay invites applications for a First Stage Researcher (R1) to explore oscillation properties of the claustrum neural network. The role combines experimental work (electrophysiology, optogenetics, imaging) with data analysis and modelling.

Responsibilities include experimental workflow from brain dissection to patch-clamp/MEA recordings, data analysis, and preparing results for publication using

Qualifications

• Solid knowledge of neuroscience from single neurons to networks.
• Experience with small-animal brain surgery for slice preparation and maintenance.
• Extensive electrophysiology experience (patch-clamp, current- and voltage-clamp); calcium imaging.

Responsibilities

• Complete ongoing in vitro experiments on the claustrum and prepare them for modelling and publication.
• Data analysis and modelling of electrophysiological results; contribute to publications.
• Format and write results for dissemination in publications.

Skills

Python programming

Data analysis

Modelling

Electrophysiology

Neuroscience knowledge

Education

Designer-level diploma

Surgery certification

Tools

Patch-clamp

MEA recordings

Calcium imaging

Job description

Organisation/Company CNRS Department Institut des Neurosciences Paris-Saclay Research Field Neurosciences Biological sciences Researcher Profile First Stage Researcher (R1) Application Deadline 28 Nov 2026 - 23:59 (UTC) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 10 Jan 2027 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Exploration and modelling of the oscillation properties of a biological neural network: the claustrum. Experimental work (electrophysiology, optogenetics, imaging), data analysis, modelling of the results obtained using AdEx neural networks and mean-field models.
Full command of the experimental workflow, from brain dissection, slice preparation and artificial survival maintenance, to patch-clamp or MEA recordings of neurons, pharmacological and optogenetic interventions, slice incubation and calcium imaging.
Data acquisition, results analysis; proficiency with the CNRS Emmy AI and use of data in the context of modelling. Formatting and writing of results in the form of a publication.

Experimentation and modelling. Mouse brain dissections for sampling (EVP), complementary electrophysiological recording experiments on brain slices in order to complete a publication. Data analysis. Modelling of the electrophysiological properties of claustrum neuron subtypes, based on the results obtained, with a view to preparing a publication.

The ANR CLAwaves project brings together four research teams, two experimental and two computational, and has funded the research of this programme. The programme in which this position is now situated consists in completing the exploration of the oscillatory properties of the claustral neural network in order to extract the mechanisms at the cellular and synaptic scales, and then to integrate them into simulations at different scales (population, mean-field, virtual brain). The role will consist in completing the ongoing in vitro experiments on the claustrum and preparing them for modelling and for a publication to be submitted within four months of the postdoc.

A solid knowledge of biological principles in neuroscience, from single neurons to neural networks. Competence in small-animal surgery for the preparation of brain slices, with a designer-level diploma and surgery-level certification. Extensive practice of electrophysiology techniques (dual patch-clamp, current-clamp, voltage-clamp, optogenetics, MEA), calcium imaging and immunohistochemical labelling (Biocytin staining; antibodies; staining). Dual biology-computer science competence, with at least proficiency in the Python language and experience in modelling (AdEx and mean-field models).