Postdoc Positions at LIONS
Epfl
Lausanne, CH
vor 3 Tg.

Working for the Ecole polytechnique fédérale de Lausanne (EPFL) means being part of a prestigious school that consistently ranks among the top 20 universities worldwide.

As a public university dedicated to improving the world around us, we have three missions : training, research and technology transfer.

We boast one of the most dynamic university campuses in Europe and employ more than 6,000 people. Our employees perform high-

value-added work in teaching and research and in the school’s administrative and technical services. Between our main campus in Lausanne and our satellite campuses in Geneva, Neuchâtel, Fribourg and Sion, our workforce is composed of more than one hundred different professions.

At EPFL, we foster a culture of respect and inclusion in the workplace. We promote a healthy work-life balance through flexible working hours and on-

campus daycare and sports facilities. Our employees also benefit from belonging to a diverse community of 16,000 people including over 10,000 students and 3,500 researchers from 120 different countries.

Postdoc Positions at LIONS

The LIONS group at EPFL has several openings for postdoctoral fellows for research in machine learning and information processing. Please see our .

We are looking for candidates with a strong theory background in machine learning, discrete optimization, information theory, statistics, compressive sensing, or other related areas.

Strong coding skills is a big plus.

There are two positions that revolve around the following two topics :

1) Bayesian optimization, bandits, and reinforcement learning

We seek to develop online algorithms for Bayesian optimization, as well as related problems such as multi-armed bandits, level-

set estimation, and reinforcement learning. The algorithms will be characterized theoretically, and also tested in real-world applications including automated hyperparameter optimization with neural networks and personalized education.

2) Discrete optimization and submodularity with applications to subsampling

We seek to develop techniques for discrete optimization, with submodularity and related concepts playing a key role. These techniques will be targeted at the application of using data in order to optimally subsample for the purpose of performing a given task, such as estimation in compressive sensing or classification in machine learning.

Specific applications will also be explored, including medical resonance imaging (MRI) with multiple coils.

LIONS provides a stimulating, collaborative and fun research environment with state-of-the-art facilities at EPFL. Personal initiative and independent research tasks related with the candidate’s interests are also encouraged.

The working language at EPFL is English. Term of employment :

Fixed-term (CDD)

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