Optimize model inference to run efficiently on our edge-infrastructure (Raspberry Pi 4). Incorporate MLOps practices to automate and streamline model deployment. Share your ML expertise and implement state-of-the-art ML best practices
Unfortunately, such testing with a full factorial variation of the parameters is not feasible. In AVL, we are developing methods for the efficient identification of critical scenarios. Performance comparison of the Machine Learning methods developed at AVL
Als Teil unseres Teams gestaltest du innovative Bildverarbeitungskomponenten für unser iriis-System. Du fokussierst dich auf die Produktentwicklung und bist für die Systemarchitektur/Interfaces unserer ML-Platform verantwortlich
Partner Call open until: October 2025 - Project start: Q1 2026 … The project concerns the development of distributed and/or federated machine-learning methods, in the context of process control, automotive industry and/or consumer electronics
Develop in-depth knowledge of acoustic emission analysis and related AI/ML techniques … Qualified degree (MSc) in mechanical engineering, electrical engineering, physics or similar - Good analytical skills combined with problem-solving orientation
Development of new generation machine learning methods focused on the detection of object, lane and driving scenarios - Integration of the developed methods into AVL platforms - Testing and analysing full self-driving stacks under different hardware and software configurations with the integrated methods
Design an agent prototype that interacts with the environment - Design dashboard prototypes to properly communicate necessary changes in resource allocation - Technologien und Skills … Knowledge of machine learning algorithms reinforcement learning)
Development of machine learning methods - Implementation of the developed methods into AVL testing pipeline of Batteries and Fuel Cells - Overcoming limitations of sparse and out-of-distribution training datasets … Ongoing studies in the fields of Computer Science, Telematics, Physics or Electrical Engineering
Performance comparison of the Machine Learning methods developed at AVL … Analysing the methods by using cognitive testing methods available in the literature on a publicly available AD stack like Autowave and Apollo … Ongoing studies in the fields of Computer Science, Telematics, Physics or Electrical Engineering
For the application of testing autonomous driving systems under different driving conditions, AVL is developing various machine learning components that are integrated into complex virtualized testing environment or used together with well-accepted ADAS/AD …