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
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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 …
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The course also equips participants to design and implement high-impact AI business cases tailored to Oil & Gas. Drawing on top-tier consulting methodologies, they will learn how to translate advanced AI solutions into tangible strategic value, directly supporting broader digital transformation initiatives within their …
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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
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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
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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
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Partner Call open until: October 2025 - Project start: Q1 2026 - Distributed learning for process optimization … Objectives … The Embedded Systems Research Division is actively seeking collaboration for a project focused on developing innovative methods and algorithms for decentralized analysis of online data streams
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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
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TU Graz master student of information and computer engineering, sound engineering or similar … Software development background for computationally efficiently processing - Knowledge of Julia will be a plus - Ideally you combine the work with a Master’s thesis
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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
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