What we offer you - Automotive companies are intensively developing automated driving functions and vehicles. Unfortunately, we have already seen severe road accidents involving automated vehicles … Performance comparison of the Machine Learning methods developed at AVL
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 …
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
What we offer you - Fitting Physical Models to the test measurements of the Batteries or Fuel Cells are a powerful tool in capturing their inner characteristics. However, the fidelity of the physical model is highly dependent on the set of physical phenomena coved by mathematical formalism
What we offer you - Batteries, being the most valuable and defining component of electric vehicles (EVs), are of paramount importance to future mobility. The demand for battery testing facilities is soaring, with capacities being reserved years ahead … Knowledge of machine learning algorithms (e.g
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
Analyze and adapt data models for battery testing - Implement simple test environment to simulate battery test lab - Analyze state of the art in ML applicable to plant management - Select appropriate approaches and implement prototypes for tasks in the battery testing facility (e.g
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
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