Postdoctoral Fellow in Machine Learning & Computational Neuroscience

We are  seeking a creative and  motivated postdoctoral fellow  to join a
multi-institution  team  embarking on  a  five-year  project to  advance
Artificial Intelligence using  principles derived from Neuroscience. The
postdoc  will  be  expected  to  help  develop  novel  machine  learning
algorithms, and  attempt to  discover principles that  bridge artificial
and  natural  intelligence.  These  efforts will  draw  on  cutting-edge
neuroscientific    data   collected   by    a   team    of   experienced
experimentalists.

The  applicant  will join  a  team  of  leading researchers  in  machine
learning, statistics,  and computational neuroscience.   The appointment
will be  at the University of  Toronto, working with  Raquel Urtasun and
Richard Zemel, but the candidate  is expected to closely collaborate and
regularly visit  the other groups: Matthias Bethge  (U. Tübingen); Ankit
Patel, Richard Baraniuk, Xaq Pitkow, Andreas Tolias (BCM/Rice); and Liam
Paninski (Columbia U.).

Applicants should  hold a  PhD in computer  science and are  expected to
have   a   strong  publication   record   in   major  machine   learning
conferences.  Remuneration is competitive  and commensurate  with skills
and track record.

The  position  is  available   immediately,  with  an  initial  one-year
appointment and an expectation of  extension to at least two years given
satisfactory performance.

To apply, please  send your CV along with a  short statement of research
interests to zemel@cs.toronto.edu, and urtasun@cs.toronto.edu.