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 (, 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


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).


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.


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

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