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.
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.
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