Open position in Machine learning and computer vision
The Idiap Research Institute, affiliated with École Polytechnique
Fédérale de Lausanne, seeks one PhD student in statistical learning to
develop original active-learning techniques to collect and leverage
very large training sets for image classification and object
This position is funded by a grant from the Swiss National Science
Foundation, and the candidate will be a doctoral student at EPFL.
Research will be done under the supervision of Dr. François Fleuret.
Recent advances in Machine Learning aim at leveraging very large
training sets. The objective of this project is to adapt
state-of-the-art supervised learning methods to use partially
annotated training sets, and to exploit structures known a priori on
the said sets to concentrate computation during learning on the most
difficult and informative subsets of data.
The application domain will be image classification and object
detection in natural images. This work will mix theoretical
developments in statistical learning with the implementation of
algorithms working on real-world data.
Applicants must be self-sufficient programmers and have a strong
background in mathematics. They should be familiar with several of the
following topics: probabilities, applied statistics, information
theory, signal processing, optimization, algorithmic, and C++
* About Idiap
The Idiap Research Institute is located in Valais, a scenic region in
the south of Switzerland, surrounded by the highest mountains of
Europe, and within close proximity to Lausanne and Geneva. The working
language of Idiap is English.
Please contact firstname.lastname@example.org for additional information.