Goal and background

With main drivers the privacy risks and power constraints, future large scale ultra dense sensor deployments open new fields for distributed AI. Novel AI mechanisms need to simultaneously execute processing and communication at the wireless edge meshes. They are expected to prevent data leaks to more centralized points, simplify wireless tranceivers (hence power consumption) and use non-explicit cues for inference within the context and environment of data sources.

TU/e, as part of a large multinational european consortium DAIS, will investigate novel ways to use non-linearities in wireless medium, tranceivers and transmissions to simultaneously enable communication and computation. The project, Distributed Artificial Intelligent System (DAIS - G.A. 101007273), was funded by the ECSEL Joint Undertaking (ECSEL JU) and a multitude of countries: Sweden, Netherlands, Germany, Spain, Denmark, Norway, Portugal, Belgium, Slovenia, Czech Republic, Turkey.

DAIS aims, besides others, at:

• providing intelligent processing and communication locally at the edge to enable real-time and safety-critical industrial applications, and
• distributing and dividing the complex AI operations between the cloud and edge, with edge undertaking early intelligent data processing reducing the bandwidth of data being transmitted to cloud.

Research Challenges

TU/e envisions low-power wireless meshes as swarms of computing and communication units able to collectively approximate any non-linear function. Instead of packing more capacity per device or link, we will study novel AI paradigms which simultaneously harvest both the complexity of neural networks and their environment they operate in. This allows transforming input data to a hyper dimensional space at a lower power consumption.

Role

The candidate will analytically and experimentally study the transformative power of the wireless medium and channel conditions on wirelessly distributed neural networks. Should this be well understood, the next step is to devise ways to use and control this power to improve the processing capabilities of wireless meshes. This work sits at the intersection of wireless communications and artificial intelligence involving embedded systems, signal processing, advanced networking, recurrent and spiking neural networks.

Work environment

Eindhoven University of Technology (TU/e) is one of Europe's top technological universities, in the heart of one of Europe's largest high-tech innovation ecosystems - the Eindhoven Brainport region. Research at TU/e is a combination of academic excellence and a strong real-world impact through close collaboration with regional and international high-tech industries.

The candidate will be employed within the Electro-Optical Communications Group (ECO), in particular within the advanced network management and control laboratory. The candidate will strongly interact with the ECO group, which consists of over 70 researchers. This position is embedded within the Center for Wireless Technology (CWT/e) at TU/e which focuses on four programs: Ultra-High Data-Rate Systems, Ultra-Low Power and Internet-of-Things Communication, Terahertz Technology, and Radio Astronomy.

We are looking, therefore, for one strong Ph.D. researcher to:

Collaboration - Continuously interact with other ECO researchers and with DAIS' partners and other users.

Dissemination - Contribute to the project reporting, scientific publications and other activities related to the preparation of new grant proposals to national and European projects.

The Ph.D. researcher should demonstrate:

• Self-drive, proactivity, curiosity and execution power.
• Creativity and critical thinking and an ability to cooperate with internal and external partners.
• Master of Science degree in Computer Science or Electrical Engineering with excellent grades in related courses.
• Deep understanding in wired/wireless communications and network implementations.
• Strong theoretical and practical knowledge and experience with artificial intelligence techniques, esp. recurrent neural networks and reinforcement learning.
• Interest in combining theory and experiments and well-developed analytic skills.
• Excellent communication skills.
• Excellent proficiency (written and verbal) in English.

• A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
• A full-time employment for four years, with an intermediate evaluation after one year.
• To support you during your PhD and to prepare you for the rest of your career, you will have free access to a personal development program for PhD students (PROOF program).
• A gross monthly salary of € 2.395,00 in the first year and € 3.061,00 in the last year (on a fulltime basis). The salary is in accordance with the Collective Labor Agreement of the Dutch Universities.
• Benefits in accordance with the Collective Labor Agreement for Dutch Universities.
• Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
• A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
• Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.