Multiple postdoctoral and PhD
positions are available in an ERC-funded project exploring
deep-learning implementations of the Global Workspace theory.
We are seeking highly motivated and dedicated students and post-docs
to join our group in Toulouse, France. Successful candidates will
have formal training in AI, Computer Science or related fields (e.g.
computational neuroscience), and a keen interest in cognitive
neuroscience. Our ERC Advanced Grant "GLoW" aims to take inspiration
from neuroscience and cognitive theories to build deep neural
network models of cognition, capable of integrating or "grounding"
information across sensory and linguistic modalities, and of
displaying flexible cognitive behavior. We will also use advanced AI
models to improve the decoding and understanding of brain activity.
Details on the ideas that will be developed in the project can be
found in this Opinion paper. The project is headed by
Rufin VanRullen (CNRS, Toulouse, France), with external advisors
Ryota Kanai (Araya, Tokyo, Japan) and Murray Shanahan (ICL/Deepmind,
London, UK).
Our lab
is part of the CerCo Institute as well as the recently
created Artificial and Natural Intelligence
Toulouse Institute (ANITI). Our team has many opportunities to
collaborate with neuroscientists, computer scientists, linguists,
roboticists etc. We have direct access to fMRI recording facilities
and to in-house (GPU) computing clusters as well as
research-dedicated supercomputers.
Typical appointments for post-docs are for 2 years (renewable for a
3rd or 4th year), and 3-years for PhD. The beginning post-doc salary
is 2,590 Euros/month (net), and can reach 3,200 Euros/month (net)
for more experienced post-docs. The PhD stipend is 2,000 Euros/month
(net). We expect to hire several candidates by the Fall of 2023, but
will continue to recruit exceptional applicants in the foreseeable
future. To apply, please send
a CV and a letter explaining your research interests and
motivations to: rufin.vanrullen [at] cnrs.fr
Any questions should also be directed to the same address.
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