University of Bordeaux

Research profile title: Artificial intelligence for neuroscience

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This scheme aims to facilitate the recruitment of young lecturer-researchers on the basis of job profiles pre-identified by the institution in emerging and highly multidisciplinary disciplines or where there are strong international stakes. The scheme is part of a talent management policy shared with partner institutions, particularly research organizations. Synergies with the systems of these organizations, whether ATIP-Avenir or "Inria Starting Faculty Position", will be sought.


The chair will be funded for a period between three and five years maximum. The chairholder will be first recruited on a fixed-term contract as a lecturer-researcher during which his or her work is monitored and evaluated (evaluation at 3 years and then at the end of the chair). If the evaluations are successful, the University of Bordeaux will then publish a statutory position. This recruitment will be carried out via the traditional competitive procedure.


The funding will cover the salary of the project leader for a maximum of 5 years (3-year fixed-term contract renewable for 2 years after evaluation; or 3 years + 1 year, 2 years + 2 years; 2 years + 1 year depending on the situation). In addition, as this is an attractiveness scheme targeting the teaching and research profession, a teaching service with a minimum of 64 hours/year may be requested.

Project-related costs such as running costs, equipment and for the recruitment of staff dedicated to the project, may complete the Chair's budget. This can be done either within the framework of this program or within the framework of external funding (regional chair, Atip Avenir), depending on the recruitment situation.

The main stages of this scheme are explained below:

Pre-recruitment chairs

For further information on the call for applications, the eligibility criteria and the evaluation process, please refer to the Applicant’s Guide (additional documents section).

Disciplinary field(s): Artificial intelligence, Image and signal processing and analysis,

Neuroscience, Cellular neurobiology.

Targeted CNU4 section(s): 27-65-69


Research profile title: Artificial intelligence for neuroscience

Research department5: Bordeaux Neurocampus

Research Profile:

Laboratory(ies): One of the teams from the Bordeaux Neurocampus Department

Director(s) of Laboratory(ies) - contacts details:

Nathalie Sans / nathalie.sans@u-bordeaux.fr

Description of the research project:

The candidate will develop AI-assisted computational methods dedicated to multimodal and multiscale data analysis for life sciences, and neuroscience in more particular. With the increasing amount and diversity of digital data acquired in modern cell biology and neuroscience (eg. super-resolution microscopy multidimensional data, volumetric images acquired at high spatial and temporal resolution, high content screening, electrophysiology recording, circuits, behavior, etc…), there is an urgent need to develop efficient analytical tools capable to process them independently or grouped. Artificial intelligence, and machine and deep learning in particular, is certainly the most appropriate solution to help achieving this role efficiently.

The research project will consist in:

  • Developing supervised and unsupervised methods for processing and analyzing biological data of various biological samples at different scales, acquired with different modalities. Biological samples include synapses, neurons, organoids, brain slices, entire brain or mice, for which recording modalities range from electronic microscopy, light super- and high-resolution microscopy, up to behavioral imaging.
  • Writing grant applications
  • Supervision of post-docs and Ph.D. students.

The candidate will be assigned to one team of the Bordeaux Neurocampus to develop a project in the field of artificial intelligence for biology. His.Her project will be part of the GPR BRAIN_2030 Neurotoolbox, aiming to provide the Bordeaux Neurocampus teams with cuttingedge technologies to help elucidate brain structure and function across organizational levels, i.e. from molecules to neural networks.

Expected competences:

  • The candidate must have a PhD in artificial intelligence, computer science or a related field.
  • Knowledge and skills in one or several deep learning environments (Tensorflow, Keras, Torch, Caffe, etc.) are required.
  • Strong theoretical and practical knowledge in applied mathematics, image processing and machine learning.
  • Experience in life sciences and microscopy is preferred.
  • The candidate should also have experience in coordinating a research team and demonstrate the ability to work in interaction with the rich local, national and international interdisciplinary environment.

Expected scientific impact:

The arrival of a research professor in artificial intelligence for neuroscience will allow the Bordeaux Neurocampus to strengthen this rapidly expanding field. This profile, at the interface between several fields and scales of neuroscience, from nanoscoscopy to neural networks, electrophysiology and behavior, will play a catalytic role and strengthen inter-unit collaborations. He.She will also enhance interdisciplinary research with INS2I, locally, nationally and internationally.



Title of the training profile: Data processing, analysis and artificial intelligence for Neuroscience

Assignment component6College of Science and Technology

Pedagogical profile:

Pedagogical assignment (education unit): Biology faculty

Director of the education unit - contact details:

Frédéric Gévaudant – frederic.gevaudant@u-bordeaux.fr

Training courses concerned:

Master EUR Light et filière Neurophotonics

Pedagogical objectives and need for supervision:

The recruited person will join the EUR-Light teaching team to participate in master's classes.

He/she must have solid knowledge in programming, digital signal processing and artificial intelligence (AI). He/she should be able to teach in English and be fluent in French. He/she will be asked to offer teaching linking modern computational approaches to neurosciences applications (ie. nano- and microscopy, electrophysiology, circuits, etc..). Ideally, the teaching should cover programming (algorithmics, Python, LabView), signal processing (1D, 2D andnD) and Artificial Intelligence (machine and deep learning) for multidimensional data processing and predictive analysis. The teaching should cover state of the art in these fields, as well as a recent innovative development and their potential application to neuroscience, AI being a very active field taking a more and more important place in fundamental research.

4 Website of the national council of universities (CNU) : https://conseil-national-des-universites.fr/cnu/#/

5 Description of the research departments : https://www.u-bordeaux.com/Research/Research-departments

6 Description of the training structures: https://www.u-bordeaux.com/Education/Colleges-Institutes

Job details

Research profile title: Artificial intelligence for neuroscience
351 cours de la Libération Talence, France
Application deadline
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