PhD in deep machine learning for multi-sensor scene reconstruction

The Idiap Research Institute invites applications for one PhD position in machine learning for computer vision at the Idiap Research Institute and École Polytechnique Fédérale de Lausanne (EPFL).

The Idiap Research Institute, affiliated with EPFL, seeks a PhD student in machine learning to develop original techniques for multi-sensor fusion, active sensing, and 3D reconstruction.

The candidate will be a doctoral student at EPFL, working under the supervision of Dr. François Fleuret at the Machine Learning group of the Idiap Research Institute.

The development of intelligent image sensing for autonomous vehicles, augmented reality, and computational photography requires the combination of multiple signals coming from different sensors. Deep-learning models have demonstrated their efficiency for these tasks, but requires a careful design of their architectures and training procedures. This project aims at investigating novel approaches to unify active and passive sensors for scene understanding and reconstruction.

Applicants must be self-sufficient programmers, and have a strong background in mathematics. They should be interested in, and familiar with, applied probabilities, signal processing, optimization, algorithmic, and deep-learning software frameworks.

The Idiap Research Institute is located in Valais, a scenic region in the South-West of Switzerland, surrounded by the highest mountains in the Alps, and within close proximity to Lausanne and Geneva. The working language of Idiap is English.

Interested? Please submit your candidature through the Idiap online recruitment system:

PhD in deep machine learning for multi-sensor scene reconstruction