Here is a list of (funded) interships proposals for the year 2016-2017.

These are intended for Master 2 or outstanding Master 1 students, and open the possibility to start a PhD. If you are interested, go ahead and contact me directly.

I also propose PhD topics. The best way for this is to discuss with me. Here are a few examples:

  • Sequential prediction of confidence sets for non-stationary signals:
    This is a highly theoretical topic, however with huge applicative potential. This topic requires a strong candidate trained in Mathematical Statistics, with focus on Model selection, Information Theory, Concentration inequalities, and Signal Processing. A descent knowledge of a programming language such as Python and some basic machine learning library is a plus.
  • Robust max-flow learning for computational sustainability:
    This topic is fairly balanced between theory and practice, and is opening a new application domain with huge societal interest. It requires a strong candidate trained in Reinforcement Learning theory and/or Control theory, proficient in Graph theory and having excellent programming skills. Good knowledge of statistical learning is also assumed.

In case you want to apply for a PhD, I strongly encourage you to read (a substantial part of) the following books and lecture notes:


Lecture Notes


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