[visionlist] Two PhDs and two Post-doc positions in Neuro-inspired Deep Learning with T. Serre & R. VanRullen

[Rufin VanRullen]

Two PhDs and two Post-doc positions in Neuro-inspired Deep Learning with 
T. Serre & R. VanRullen
[Apologies for cross-postings]

We are seeking talented and motivated students and post-docs for a 
number of open positions, in a collaborative effort between the labs of 
Thomas Serre (Brown University/Toulouse) and Rufin VanRullen (Toulouse). 
The positions will be based in Toulouse (France), with numerous 
opportunities to travel, in particular for visits to and close 
collaborations with the Serre lab at Brown University (USA). The 
successful candidates will become involved in a number of projects, 
depending on their particular interests, and will also have the 
opportunity to develop independent projects.

Applicants for the PhD positions should hold a Masters degree or 
equivalent. Applicants for the post-doc positions should hold a PhD, or 
expect to receive their PhD shortly. Candidates must have a strong 
background in computer vision and/or computational neuroscience and/or 
machine learning. Excellent python programming skills and 
Tensorflow/PyTorch experience are required. Additionally, applicants at 
the post-doc level should ideally have a track record of relevant 
publications at top venues (e.g., NIPS, ICML, CVPR, ICCV, ICLR, etc.). 
Exceptional candidates with a primary degree in Neuroscience and strong 
programming/quantitative abilities will also be considered.

The fellows will be located in a state-of-the-art facility within the 
new ANITI (Artificial and Natural Intelligence Toulouse Institute) 
research center in Toulouse, France. They will be part of the AI 
Research Chairs held by Thomas Serre ("Reverse-engineering the brain") 
and Rufin VanRullen ("Deep Learning with semantic, cognitive and 
biological constraints"). They will also benefit from a lively local 
community of Deep Learning researchers: the Toulouse Interdisciplinary 
Deep Learning "TIdDLe" group (https://tiddle-group.github.io).

Perks include: competitive salaries, clement weather, high quality of 
life, vibrant research environment.

To apply, send a CV, a short (<1 page) explanation of research 
interests, and the name of 3 potential referees to 
thomas_serre at brown.edu and rufin.vanrullen at cnrs.fr

The positions start in Fall 2019 (later start dates can be negotiated), 
the application procedure is and will remain open until all positions 
are filled.

For more information about ongoing research projects in our labs, 
consult: http://serre-lab.clps.brown.edu/ and 
http://cerco.ups-tlse.fr/~rufin/

Some relevant papers:

D. Linsley, J. Kim, & T.  Serre. Sample-efficient image segmentation 
through recurrence. ArXiv 2019. https://arxiv.org/abs/1811.11356

D. Linsley, J. Kim, V. Veerabadran, C. Windolf & T. Serre. Learning 
long-range spatial dependencies with horizontal gated-recurrent units. 
Neural Information Processing Systems, 2018. 
https://neurips.cc/Conferences/2018/Schedule?showEvent=11042

D. Linsley, D. Schiebler, S. Eberhardt & T. Serre. Learning what and 
where to attend. International Conference on Learning Representations, 
2019. https://openreview.net/forum?id=BJgLg3R9KQ

VanRullen, R., Reddy, L. (2019). Reconstructing Faces from fMRI Patterns 
using Deep Generative Neural Networks. Nat Comm Biol. 
https://www.nature.com/articles/s42003-019-0438-y

VanRullen, R. (2017). Perception Science in the age of Deep Neural 
Networks. Front. Psychology 8:142. 
https://www.frontiersin.org/articles/10.3389/fpsyg.2017.00142/full

McLelland, D. & VanRullen, R. (2016). Theta-Gamma Coding Meets 
Communication-through-Coherence: Neuronal Oscillatory Multiplexing 
Theories Reconciled. PLoS Comput Biol 12(10), e1005162. 
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005162 


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