PhD in machine learning for air traffic control

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

The Idiap Research Institute, affiliated with EPFL, seeks a PhD students in machine learning to develop original techniques for weather and trajectory forecasting in the field of air traffic control.

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.

Air traffic involves the tracking of aircrafts and the optimization of their trajectories under strict safety constraints. The availability of a fine weather forecasting and better assessment of the dynamic of the aircrafts is key to solving this complex problem. This project aims at developing deep-learning based approaches to take advantage of large amounts of available historical data, and produce models more efficient than current ad hoc methods.

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 machine learning for air traffic control...