Le cerveau multidimensionnel

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POSTDOC position at UNIC

1- Postdoc or Engineer position : Multi-dimensional data visualization.

 

 

 

 

 

 

The BRAINSCOPES program funded by the Paris-Saclay University is looking for a talented scientist to work in a collaborative project supervised by Thomas Deneux of the CNRS Unit for Neurosciences, Information and Complexity, (UNIC). Modern neurophysiology recordings generate large amount of data, requiring both sophisticated preprocessing and analysis techniques and powerful visualization tools that allow a flexible and intuitive exploration of the data’ structure. The UNIC laboratory has started to develop a visualization program, XPLOR, which offers a smooth navigation and fast extraction of meaningful information across multiple data dimensions. Although it is currently used for neurophysiological imaging (see ref. [1,2]), this program is generic and has a potential for applications beyond this field.

The position will aim at further developing this program :
- consolidating the existing functionalities by translating XPLOR from Matlab to Python (or C++),
- adding pattern recognition (e.g. clustering), machine learning methods (regression models, SVM classification, possibly deep learning methods) to extract regularities in the data.
The work will involve collaborations with different teams of the Paris-Saclay Institute of Neuroscience who will use the software, and further diffusion through publications, conferences, collaborative code sharing.
The position is immediately available for one year, potentially renewable and is open to candidates with strong skills in programming and machine learning having interest for neurobiology research.

To apply, please contact Thomas Deneux.

- PDF

 

References :
[1] Deneux et al. Accurate spike estimation from noisy calcium signals for ultrafast three-dimensional imaging of large neuronal populations in vivo. Nature Communication 2016.
[2] Deneux, Kempf et al. Temporal asymmetries in auditory coding and perception reflect multi-layered nonlinearities. Nature Communication 2016.


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