PhD Studentships in Probabilistic Machine Learning @ EPFL

[Matthias Seeger]

Two PhD studentships are available in the

  Probabilistic Machine Learning group [headed by Matthias Seeger]
  School of Computer and Communication Sciences
  Ecole Polytechnique Federale de Lausanne (EPFL)
  http://lapmal.epfl.ch/

The group focusses on the development and analysis of scalable Bayesian
inference and graphical modelling technology, Bayesian experimental design
(Bayesian active learning), Bayesian learning (or model calibration) and
robust estimation, with applications in medical imaging, low level computer
vision and bio-informatics.

The group is part of one of Europe's highest ranked computer science faculties
at EPFL, one of the leading technical universities worldwide. EPFL is
beautifully located between Lake Geneva and a stunning mountain scenery, with
ample opportunities for recreational activities. The Lausanne area is known
for its numerous cultural festivals. PhD salaries are internationally
competitive and among Europe's highest.

Openings are available for exceptional students who are able to demonstrate
their motivation and abilities for machine learning research:

- Excellent mathematical background, in particular in probability,
  continuous mathematics (physics background highly desirable), or continuous
  optimization
- Prior exposure to concepts of modern probabilistic machine learning, as
  conveyed by (f.ex.) textbooks by C. Bishop, D. Barber, or K. Murphy. A solid
  understanding and working knowledge in this area is highly desirable

Admission to the doctoral program is internationally competitive.
Application to the doctoral program EDIC is centralized. Please refer to

  http://phd.epfl.ch/page-19698-en.html

for any details concerning the application process. The deadline for
applications is

  January 15, 2013

Note that while EDIC admits PhD students once a year only (October 2013),
the possibility to start earlier is given.

You are encouraged to send your complete application file beforehand to

  matthia...@epfl.ch

Please make sure to include two samples of independent work of yours, which
demonstrate your best efforts and abilities in line with the requirements of
this call. This could be:

- Published papers (preferably first author)
- Term papers for projects
- MS or BS thesis
- Samples of machine learning related code
- Link to a website where such material can be downloaded

Relevant links:

- EDIC doctoral school:
  http://phd.epfl.ch/page-19698-en.html
- Research in the Probabilistic Machine Learning group:
  http://lapmal.epfl.ch/
- Computer and Communication Sciences, EPFL:
  http://ic.epfl.ch/