We are looking for a candidate for a 3-year industrial PhD position (CIFRE) on a topic which is at the crossroad between artificial intelligence and control engineering.
The topic of the PhD is developing correct-by-design, explainable AI algorithms for detecting and predicting abrupt changes of human/rider motion using methods from control engineering and machine learning. More precisely, we plan to use domain knowledge to build gray-box dynamical models, estimate the parameters of those models by using algorithms from control engineering (system identification) and use these models in combination with Machine learning algorithms to predict different interesting movement-related events. Moreover, we plan to derive theoretical results explaining when and why these algorithms work, so that they could be used in safety-critical applications, in which these algorithms are expected to be explainable. In addition to theoretical research, the candidate is expected to work on various concrete case studies and products involving real-time crash detection of two-wheeled vehicles for various safety-related applications.
The ideal candidate should have a background in one or more of the following disciplines: artificial intelligence/machine learning, control engineering, systems identification and signal processing. A solid background in mathematics is a must. Prior experience in machine learning is highly desirable. Good proficiency of English orally and in writing is also required to publish and present results effectively at various suitable venues both internal and external.
The project is a joint collaboration between University of Lille/CNRS and Autoliv.
Within Autoliv, the PhD project is a collaboration as well between the advanced development organization in France and the global research organization located in Sweden. This project includes the opportunity to really see the research transform into useful application within an industrial company. The prospective student will be hired by Autoliv. The expected starting date is June 1, 2022.
Documents required for application:
- A motivation letter.
- An up-to-date CV.
- At least two recommendation letters from previous teachers.
- Grades obtained during your last 3 years of graduate studies and program of courses attended by students graduated from a university abroad if available.
- Copy of your personal works (internship reports, professional experience, employment contracts, etc...) if available.