Assistant/associate professor position in Efficient Machine Learning (V36.3777)

Assistant/associate professor position in Efficient Machine Learning

The Electronic Systems Group of the Department of Electrical Engineering at Eindhoven University of Technology (TU/e) invites applications for a tenure-track assistant/associate professor position in Efficient Machine Learning / Deep Learning. The position is open immediately, but the start date is flexible.
Aanstellingsfunctie(s)
Universitaire hoofddocent, Universitaire docent
Faculteit(en)
Faculteit Electrical Engineering
FTE
1,0
Sluitdatum
25/08/2019
Aanvraagnummer
V36.3777

Functieomschrijving

Assistant/associate professor tenure-track position in Efficient Machine Learning / Deep Learning

Job description
TU/e is a highly ranked university in both research and teaching. Basic and the application-inspired research are equally valued. TU/e is often ranked exceptionally high based on scientific co-publications with industry and the impact of its scientific research.

TU/e has identified Artificial Intelligence (AI) as one of the key multi-disciplinary research opportunities in the taskforce TU/e 2030. Various research groups at Computer Science, Electrical Engineering, Mechanical Engineering and other departments of TU/e have been active and visible within the area of AI and their applications. There is an ongoing initiative, both at the university level and the department level, to strengthen our research and education in this direction.

The Electronic Systems group in the department of Electrical Engineering is looking for one Assistant/Associate Professor in Efficient Machine Learning (ML) or Deep Learning (DL) who has an ambition to build his/her own research lab in this area.

The Electronic Systems group consists of seven full professors, ten assistant professors, several postdocs, about 50 PDEng and PhD candidates and support staff. The ES group is world-renowned for its design automation and embedded systems research. It is our ambition to provide a scientific basis for design trajectories of electronic systems, ranging from digital circuits to cyber-physical systems. The trajectories are constructive and lead to high quality, cost-effective systems with predictable properties (functionality, timing, reliability, power dissipation, and cost). Design trajectories for applications that have strict real-time requirements and stringent power constraints are an explicit focus point of the group.

Your profile:
We search for top candidates in machine learning / deep learning who are interested in contributing to scientific innovations and break-throughs, especially for energy and resource efficient ML/DL algorithms and circuits. The precise research focus will be left to you, to your personal research interests and preferences.

As a newly appointed faculty member, you will be working in the Electronic Systems group with the opportunity to start your own lab on ML/DL in this group. Next to your research quality, your educational skills are very important since we expect you to develop and teach ML/DL courses at all levels. 

Functie-eisen

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 Computer Science or Electrical Engineering.
  • Publications in top journals and conferences, reflected through a high H-index score.
  • Excellent communication, organization and leadership skills demonstrating the potential of building an own research group.
  • Strong cooperation 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 as 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 an emerging area of Machine Learning.

Arbeidsvoorwaarden

We offer:

  • a challenging job in a dynamic and ambitious university;
  • a tenure track appointment for a period of five years;
  • a salary depending on your experience and according to Dutch CAO (a starting salary of an assistant professor is € 3.637);
  • 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);
  • assistance for finding accommodation;
  • a broad, attractive package of fringe benefits (including an excellent technical infrastructure, child care, and excellent sports facilities).

Informatie en sollicitatie

If you are interested in working in an exciting, dynamic, high-tech environment, where you will contribute to creating the society of the future, then apply through the button on this page and upload an extended curriculum vitae including a complete publication list, a well-motivated application letter, a research statement, a teaching statement, and the three publications that you consider your most valuable work so far. We look forward to working with you!

For more information on the position, please contact prof.dr. H. Corporaal (h.corporaal[at]tue.nl) or prof.dr.ir. Twan Basten, chair of the Electronic Systems group (a.a.basten[at]tue.nlhttp://www.es.ele.tue.nl/~tbasten).

For more information on working at the TU/e and employment conditions, see https://www.tue.nl/en/careers/working-conditions/ or contact Mr. Twan Janssen, Recruiter,  a.p.c.j.janssen[at]tue.nl, (tel. +31 40 247 6347).  

You can respond to this vacancy via our application page www.tue.nl/jobs by clicking on the button "Solliciteer op deze vacature / Apply for this job". We do not respond to applications that are sent to us in a different way.

You can upload a maximum of 5 documents of up to 2MB each.

The selection of applicants and the job interviews will start immediately until we find a suitable candidate.

For this vacancy we will recruit simultaneously both internal as external. In the case of equal suitability internal candidates take priority over external candidates. An assessment can be part of the selection procedure.

Acquisition as a result of this advertisement is not appreciated.