The Advanced Networking laboratory at Electrical Engineering (EE) department of TU/e has one Ph.D. position in the field of wireless networks and distributed AI.

Goal and background

Orbiting satellite swarms or disaggregated spacecrafts open new fields for distributed AI. Novel distributed AI mechanisms need to simultaneously help on situational awareness and problem solving at runtime while constrained in processing and communication capacity. Wireless orbiting sensors deployed in high densities can offer robustness in case of failures/power outages or even insufficient computing/communication resources. Several state-of-the-art proposals focus on some type of data aggregation to (semi-)centralized entities. However, proactively orchestrating such distributed systems lacks attention. Swarm/spacecraft management should be a joint optimization problem of networking and computing resources. TU/e will focus on designing computing paradigms based on AI inherently distributed across dense large-scale wireless low-power networks.

TU/e is leading a Dutch consortium, Autonomous Distribution Architecture on Progressing Topologies and Optimization of Resources (ADAPTOR), which investigates novel ways to optimally share computing across constraint flying/orbiting swarms. The swarm requires continuous observation of its status to keep its sensing capabilities optimal. Several functions which execute in every sensor need to coordinate and collectively decide on adjusting sensing resolution, data recovery and more. Yet, these functions might be interrupted; function migration at runtime given the wireless network paths and computing capacity of other sensors requires joint optimization of the wireless network and the compute resources. The project was funded by the Dutch Organisation for Scientific Research (NWO) and Thermo Fisher Scientific in cooperation with ASTRON.

ADAPTOR aims, besides others, at providing intelligent computing and communication strategies locally at micro-satellite swarms to minimize the data volumes to be transferred to Earth. Several maintenance and functional services need to be computed completing at runtime a multitude of non-linear approximations. Yet, the scarcity of resources (compute, storage and communication) at those distributed instruments require novel computing approaches. 

Role

The candidate will analytically and experimentally study the use case of orbiting low frequency array and its operating functions. The aim to investigate thetransformative power of the wireless networks on distributed neural networks. Should this be well understood, the next step is to devise ways to use and control this power to improve the collaborative 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 networking 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 PhD researcher to:

Collaboration - Continuously interact with other ECO researchers and with ADAPTOR's 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.

Qualifications

The PhD 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 (e.g. wireless communications, networks, AI/ML, distributed systems)
• 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, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities.
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.