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PhD position on Artificial intelligence for indoor context recognition

PhD position on Artificial intelligence for indoor context recognition

Interesting PhD position on Artificial intelligence for indoor context recognition at TU/e.
Mathematics & Computer Science


The Computer Science Department of Eindhoven University of Technology has a PhD position in Artificial Intelligence (AI) for intelligent context aware lighting in the Interconnected Resource- aware Intelligent Systems (IRIS) group. The PhD candidate is to work in the multidisciplinary IntelLight project that is in collaboration with Signify.

For intelligent lighting control to accommodate user needs and preferences in different contexts, algorithms are needed to infer, and predict ahead of time, a user's context. Artificial Intelligence (AI) approaches such as machine learning are widely used in solutions of context recognition in the literature. IoT connectivity makes AI solutions even more interesting since it enables much more contextual information around a user by unlocking data from all sorts of IoT-enabled sensors (not necessarily owned by the user) and directly from the Internet. To be successful, human activities and contexts need to be recognized accurately based on noisy (mostly unlabeled) data. In the PhD candidate’s task is to develop highly accurate, realistic, deployable and robust algorithms for context recognition at homes, while considering the diversity of environments and privacy considerations of users. This is a framework that enables adequate intelligent lighting applications outside of controlled laboratory settings. It does this by solving the issues arising from considerations around the typical lack of labelled training data, data imperfections, diversity of sensor types, models and topology and, last but not least, user privacy.

We are looking for candidates that would like to tackle these challenges and to build a framework that enables intelligent lighting applications outside of controlled laboratory settings.

This position is funded by the Dutch TKI High Tech Systems and Manufacturing (HTSM). Our collaborators in this multidisciplinary project are the TU/e Department of Industrial Engineering & Innovation Sciences (Human Technology Interaction group), the TU/e Department of Mathematics (Illumination Optics group) and Signify as the main industry stakeholder.

The successful candidates are expected to:

  • perform scientific research in the domain described above;
  • publish results at (international) conferences;
  • collaborate with other group and faculty members;
  • collaborate with Signify;
  • attend project meetings and contribute to deliverables and project outcome;
  • assist with educational tasks (e.g. assist courses, supervise Master students and internships)


  • You have a strong background in machine learning, and specifically deep learning. You have some knowledge of IoT technology and networks. You have a master degree in Computer Science, (Applied) Mathematics, Information Technologies, or a related field.
  • You have good programming skills and experience (Python is an asset).
  • You have good communicative skills and are eager to work as part of a research team.
  • You are creative and ambitious.
  • You have good command of the English language (knowledge of Dutch is not required).


We offer you:

  • An exciting job in a dynamic work environment
  • A full time appointment for 4 year at Eindhoven University of Technology (
  • The salary is in accordance with the Collective Labour Agreement of the Dutch Universities, increasing from € 2.395 per month initially, up to € 3.061 per month.
  • An attractive package of fringe benefits, including end-of-year bonus (8,3% in December), an extra holiday allowance (8% in May), a personal development program for PhD students (PROOF program) and excellent sports facilities.

More information on employment conditions can be found here:

Informatie en sollicitatie

In your application, please submit:

  • Motivation letter
  • Detailed CV incl. publication list
  • MSc and BSc transcripts
  • 2 recommendation letters

For further information concerning the position, please contact Dr. T. Ozcelebi (t.ozcelebi[at]

For information about the employment conditions please contact HRServices.MCS[at]