Postdoctoral Position in Large Scale Bayesian Machine Learning

Postdoctoral Position in Large Scale Bayesian Machine Learning

Posted by Rebecca Martin on Thu, 23/06/2011 - 15:17

EPFL's Probabilistic Machine Learning Lab (http://lapmal.epfl.ch/), headed
by Matthias Seeger, has an opening for a post-doctoral fellow in the
field of Bayesian machine learning / low level computer vision, as part of
a project funded by the European Research Council.

The initial appointment is for 12 months, extensions up to 3 years are possible.
Topics of interest are:

- Variational approximate Bayesian inference, particularly for large scale
generalized linear and/or hybrid models
- Approximate inference for large structured models (stacks of image frames,
video, text), with particular emphasis on parallel computing (multi-core,
graphics processing units)
- Exploring boundaries between approximate Bayesian inference, numerical
mathematics, and large scale optimization
- Theoretical and algorithmic progress for variational Bayesian inference
- Applications of variational Bayesian inference to adaptive compressive
sensing, magnetic resonance imaging, low-level computer vision, or other
large scale domains

Position:

The successful candidate would establish approximate Bayesian computations in
domains and at scales not previously attempted. The Probabilistic Machine
Learning Lab is set within a vibrant, world-class computer and communication
sciences faculty (highest-ranked in Europe) at EPFL, one of the leading
technical universities worldwide.

EPFL is located next to Lake Geneva in a beautiful setting 60 kilometers
away from the city of Geneva. Salaries are internationally competitive (among
the highest in Europe).

Education:

Applicants are expected to have finished, or be about to finish their
Ph.D. degrees. They must have an exceptional background in probabilistic
machine learning, numerical mathematics, or statistical physics. A firm grasp
of approximate Bayesian machine learning and/or advanced (medical) image
processing is desirable. A track record of publications at top ML or CV
conferences (NIPS, ICML, UAI, JMLR, CVPR, ICCV, PAMI, IJCV) and/or top-ranked
image processing or physics journals is essential.
Further pluses are strong scientific programming skills (C++, Matlab), prior
exposure to (medical) image/signal processing practice.
The working language at EPFL is English (good skills essential), French is
not required.

Application:

Please send your applications by email to
Matthias Seeger (matthias.seeger(at)epfl.ch)

Make sure to include:
- Statement of interest
- Curriculum vitae
- List of publications (add copies of 2-3 strongest papers in the area of
interest of this call)
- Contact details for three letters of reference