Timing and Performance Modeling of AD Framework Student (R0) per el Barcelona Supercomputing Center

The objective of this position is to work and/or research in a small team of experts in timing and performance analysis of embedded critical systems, specializing in analyzing and modeling cutting-edge AI-based autonomous driving systems. The student will be mentored by experienced senior researchers, will collaborate with engineers coordinating major developments, and will interact with other students working on related topics.

The development and investigation will be focusing on industrially representative setups, deploying specialized middleware solutions, such as ROS2, CyberRT, or Autoware, on top of general-purpose and/or automotive operating systems.

The student is expected to be fairly experienced in generic programming and scripting languages (C, C++, Python, etc.) while no familiarity is required with the specific middleware solutions and operating systems. The activity assumes a preliminary familiarization phase where the student will be assisted by experienced engineers to understand and master the application environment as well as tools and techniques. Motivation, proactivity, and fast learning skills are more important than experience for this position.

Key Duties

• Contribute to the understanding and modeling of timing constraints in the execution of representative AI-based autonomous driving functions on top of state-of-the-art automotive middleware framework.
• Organize and classify possible timing constraints and related issues and exploit the developed classification to design and implement an extensive set of code patterns for intercepting timing issues within a selected middleware framework.
• Experiment with a representative application and setup to assess the proposed approach.

Data de tancament: Dissabte, 16 Març, 2024

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