Department of Electrical Engineering: Three assistant/associate professor positions in Machine Learning

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The Department of Electrical Engineering at the Eindhoven University of Technology (TU/e) invites applications for tenure-track assistant/associate professor positions in Efficient Machine learning. The start date in 2018 is flexible. The screening of applications will start on June 30th, 2018.

TU/e is a globally highly-ranked technical university, in particular with regards to collaboration with industry and the global impact of its scientific research (see https://goo.gl/3AucT3).  

TU/e has identified Artificial Intelligence (AI) as one of the key multi-disciplinary research objectives in its R&D roadmap to 2030.  In that realm, various research groups across the university have developed active and visible AI-related research initiatives over the past few years. There is an ongoing initiative both at the university board level and the faculty level to strengthen our research and education in this direction. 

We look for candidates with solid expertise in machine learning technologies who are interested in contributing to scientific innovation and education in any of the following research directions:

Efficient machine learning (ML) / deep learning (DL) systems. (This candidate will get hosted at the ES group, link):  This position relates in particular to the development of energy and resource efficient ML   networks, algorithms and circuits, and advanced mapping techniques for the efficient execution of ML algorithms and networks on different processing targets.

Machine learning for dynamical systems (Hosted at the CS group, link): addressing dynamic behavior of engineering systems and related stochastic properties in applied modelling, control and estimation problems with a strong link to applications in smart industries and high-tech systems, robotics, autonomous vehicles (cars, drones).

Intelligent information processing in streaming data (Hosted at the SPS group, link): e.g. audio, video, communication data or physiological measurements. We have an active interest in probabilistic (Bayesian) and neuroscience-inspired machine learning technology as well as deep learning technology for a wide range of signal processing applications.

As a newly appointed faculty member, you will get the opportunity to start your own lab on ML and maintain an active collaboration on the ML-related research activities at the department and beyond. Next to the quality and impact of conducted research, your educational skills are very important since we expect you to develop and teach ML courses at all levels.

We are looking for candidates that match the following profile:

A PhD degree in Artificial Intelligence, Machine Learning, Deep Learning or other relevant areas in Electrical Engineering, Computer Science, Control Engineering or Signal Processing.

A solid record on dissemination of research results with published articles in top-ranked journals and presentations at the major ML conferences.

Excellent communication, organization and leadership skills that demonstrate the potential of building your own research group.

Strong collaboration skills and ability to work in a team; successful candidates are expected to collaborate with colleagues in other fields of Electrical Engineering, as well as with colleagues from other faculties working on machine learning.

A successful candidate is expected to have a clear vision on education, and to consider teaching equally important to research. Excellent skills in developing and teaching academic courses (preferably in AI and machine learning) are essential.

A successful candidate at the Associate Professor level is expected to have an international academic reputation in a well-defined or in an emerging area of Machine Learning.

We offer:

a challenging job in a dynamic and ambitious university;

a tenure track appointment for a period of 5 years;

a salary depending on your experience and according to Dutch CLA (a starting salary of assistant professor is €3.475 per month);

a yearly holiday allowance of 8% of the yearly salary;

a yearly end-of-year allowance of 8.3% of the yearly salary;

a minimum of 41 holidays per year (excluding bank holidays, for a full-time employment of 40 hrs/week);

a broad, attractive package of fringe benefits (including an excellent technical infrastructure, child care, and excellent sports facilities).