PhD Distributed adaptive configuration of future automotive E/E architectures

•    Are you inspired by the prospect of shaping the future of automotive systems?
•     Are you fascinated by the latest developments in intelligent autonomous vehicles?
•     Are you excited to work on adaptive automotive E/E architectures?
Then apply for the PhD position on Distributed adaptive configuration of next generation automotive E/E architectures!

Automotive systems are becoming increasingly complex. Modern features like active safety features, Advanced Driving Assistance Systems (ADAS), and autonomous driving have substantially increased the demand for real-time predictable communication and computation architectures within a vehicle. Moreover, run-time changes in the vehicle, environment conditions, and driving scenarios result in the need for dynamic configuration of the data communication network and the available processing resources. This has paved the road for the Time Sensitive Software Defined Networking (TSSDN) concept to be applied for in-vehicle (wired/wireless) networks. Standard reconfiguration protocols (e.g., the YANG model) are used for configuration of various types of network devices at run-time providing an abstraction of the underlying hardware. Therefore, the architecture of the communication network within a vehicle and the scheduling of its resources can be changed over time. Accordingly, the computation resources may need to be rescheduled to fulfill dynamic needs for processing sensory data. This process of reconfiguration must be efficient, real-time, and reliable. The goal of this PhD research is to design, model and implement mechanisms for distributed reconfiguration of automotive resources in a real-time and predictable manner. Efficient artificial intelligence solutions (e.g., reinforcement learning) have promising potential to be used for this problem. The models are expected to be implemented and validated on a predictable multiprocessor platform.

Requirements:

• A master's degree (or an equivalent university degree) in computer science or electrical engineering.
• A research-oriented attitude.
• Knowledge of communication networks and software defined networking.
• Affinity for (semi)formal reasoning as well as software implementations, in particular with C++.
• Knowledge of artificial intelligence methods is a plus.
• Ability to work in an interdisciplinary team and interested in collaborating with industrial partners.
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written English (C1 level).

Salary Benefits:

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, scale P (min. €2,770 max. €3,539).
• 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.

38 hours per week

De Rondom 70