Connectionists: PhD/postdoc positions machine learning/image processing, Saarbruecken University, Germany

[Matthias Seeger]

PhD Student / Postdoctoral Researcher in Machine Learning, Image Processing

Probabilistic Machine Learning and Medical Image Processing
Saarland University, Saarbruecken, Germany

Fully-funded PhD/postdoc positions are available in the recently established
Probabilistic Machine Learning group headed by Matthias Seeger (PhD). PhD
training is conditional on acceptance to the International Max Planck
Research
School for Computer Science (based on evaluation of research proposal and
oral presentation, after first six months).

Recent breakthroughs in large-scale approximate Bayesian inference for
sparse continuous variable models allow nonlinear Bayesian experimental
design
(active learning) and compressed sensing to be applied to sampling
optimization
of magnetic resonance imaging. For details about these projects:


http://www.kyb.tuebingen.mpg.de/bs/people/seeger/projects/ed_mri/main.html

Saarland University is among the leading computer science faculties in
Europe,
with world-class groups in computer graphics, theory of algorithms and
programming languages, theoretical CS, and bioinformatics, among others. It
features a unique accumulation of top-ranked CS research institutes
(Max Planck Institute for Informatik, Max Planck Institute for Software
Systems, DFKI). Within the recently established interdisciplinary MMCI
Cluster
of Excellence, 20 independent research groups are working in areas with
strong
overlaps to core machine learning application areas.
Saarbruecken is dedicated to excellent postgraduate education, structured
according to international standards in the International Max Planck
Research
School for Computer Science (courses taught in english).

The Probabilistic Machine Learning group focusses on theory and applications
of approximate Bayesian inference, and its scalable reduction to standard
methods of scientific computing (numerical mathematics, efficient
algorithms,
signal processing, parallel computing). We closely collaborate with the
Center
for High-field Magnetic Resonance, Max Planck Institute for Biological
Cybernetics, Tuebingen (with a range of MR scanners dedicated to basic
research), and have close ties to the Empirical Inference group (headed by
Bernhard Schoelkopf) at the same institute, beyond connections to top
machine
learning groups in the UK and US.

We are looking for highly motivated, research-oriented individuals with an
excellent grasp of the mathematics underlying approximate Bayesian
inference,
or/and numerical optimization and mathematics, or/and image and signal
processing. A strong theoretical background in a field relevant to analysis
of statistical methods, or/and keen interest and capabilities in large-scale
scientific programming are required.

Please be sure to include the following in your application:
* Curriculum vitae
* Statement of research interests (1 page)
* Letters of reference (1-3) from referees able to comment on your work and
  academic standing (PhD/MSc thesis advisor, supervisor for internships)
* Sample of your strongest work (first-author paper in peer-reviewed
  journal/conference, MSc or PhD thesis, term project paper (with official
  record attesting your authorship)) in the rough area of interest
* Transcript of studies (for PhD applicants)

Applications should be sent by e-mail to Matthias Seeger,
mseeger at mmci.uni-saarland.de. If you happen to attend the forthcoming
Neural Information Processing Systems conference (Vancouver, December
8-13, 2008; http://nips.cc/Conferences/2008/), please make yourself known to
me there.

Relevant links:
* Project page
  http://www.kyb.tuebingen.mpg.de/bs/people/seeger/projects/ed_mri/main.html
* MMCI Cluster of Excellence
  http://m2ci.dl01.de/index.php?id=1&L=0
* International Max Planck Research School for Computer Science
  http://www.imprs-cs.de/
* Max Planck Institute for Informatik
  http://www.mpi-inf.mpg.de/
* Saarland University
  http://www.uni-saarland.de/en/
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