CALL FOR APPLICATIONS
POSTDOCTORAL RESEARCH SCIENTIST
Probabilistic Inference - Machine Learning - Decision Making
Statistical Computing - Bayesian Theory & Applications
Computer Vision - Coding - Speech Recognition - Bioinformatics
Our group at the University of Toronto would like to hire one or more
postdoctoral research scientists. The successful applicant(s) will
work on theoretical and applied research in areas such as those listed
above. Faculty members in our group and their interests are as follows:
Craig Boutilier http://www.cs.toronto.edu/~cebly
Markov decision processes, reinforcement learning. Probabilistic
inference. Economic models of agency, combinatorial auctions.
Preference elicitation, interactive optimization under uncertainty.
Brendan Frey http://www.cs.toronto.edu/~frey
Graphical models, machine learning, variational techniques, loopy
belief propagation. Computer vision. Speech recognition. Iterative
error-correcting decoding. SAR and MRI imaging. Bioinformatics.
Radford Neal http://www.cs.toronto.edu/~radford/
Bayesian modeling with neural networks, Gaussian processes, and
mixtures. Markov chain Monte Carlo methods. Low density parity
check codes. Empirical assessment of learning methods.
Jeffrey Rosenthal http://markov.utstat.toronto.edu/jeff/
Probability theory and stochastic processes. Markov chain Monte
Carlo theory and methods. Convergence rates of Markov chains.
Randomized algorithms. Random walks on groups.
Rich Zemel http://www.cs.toronto.edu/~zemel
Unsupervised learning, boosting. Perceptual learning,
representations of visual motion, multisensory integration.
Neural coding, probabilistic models of neural representations.
The group currently consists of the above faculty members, 2 postdoctoral
researchers and 25 graduate students and has joint projects with Microsoft
Research, Xerox PARC, the University of Illinois at Urbana-Champaign,
the University of British Columbia, the University of Waterloo, and Simon
Fraser University.
Applicants should
* have a solid background in one or more of the areas described above
* have good scientific skills
* be good at writing software to implement and evaluate algorithms
Successful applicants who wish to do so will have the opportunity to
apply to do sessional teaching in the departments of Computer Science,
Statistics, or Electrical and Computer Engineering.
Applicants should EMAIL a CV, the email addresses of 3 references, and
a short description of their research interests and goals as a postdoc
(ascii format, < 500 words) to Brendan Frey at frey@cs.toronto.edu.
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