Working student: Evaluation of Ethernet traces and optimization of the associated toolchain using the latest AI tools

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Number: MER00042Z9 The communication design team is responsible for all communication interfaces on standard bus systems between the control units in the vehicle. Among other things, the communication between all components is described in standardized documents. Admission Control ensures that bus load limits are adhered to and laths are ensured during transmission. You support our team in developing an internal toolchain to analyze recorded data from test vehicles. The aim is to derive descriptions and key figures that can be loaded from large amounts of data and serve as the basis for models and simulations in the vehicle context. This focuses on scalability, performance and the implementation of new requirements in the project course. These challenges include: Introduction to the existing data analysis pipeline and the associated evaluation logics

Analysis of runtime and storage bottlenecks and implementation of performance optimizations (e.g. more efficient data structures, parallelization)

Further development of the pipeline for processing very large amounts of data (robustness, scalability, monitoring/profiling)

Implementation of new requirements for models/simulations (e.g. derivation of additional parameters from raw data, extension of model logic)

Support in building tests/validations to ensure the quality of results (e.g. plausibility checks, regression tests)

Documentation of implementations and results as well as close exchange in the project team

The activity may begin after consultation.

Current studies in the field of computer science, electrical engineering, vehicle technology, mathematics, data science or comparable

Very good programming skills (e.g. Python, C++, ...)

Experience or strong interest in data analysis/processing and handling large amounts of data

Basic knowledge of performance optimization, profiling and/or parallelization are advantageous

Safe and responsible use of modern AI-based tools to support development, analysis and documentation

Ideally, knowledge in communication and/or network technology or readiness to quickly process

Careful, independent and structured operation

Analytical thinking, team skills and good communication skills

Additional information: We are looking forward to your online application with CV, lettering, certificates, current enrollment certificate, giving the semester and proof of the regular study period. Please do not forget to mark your documents as ''relevant for this application' in the online form and note the maximum file size of 5 MB. Further information on the setting criteria can be found here. Disabled and equalized applicants are welcome! The severely disabled representative (sbv-sindelfingen@mercedes-benz.com) is happy to support you in the application process. HR Services will be happy to help you with questions about the application process. You can reach us by email via myhrservice@mercedes-benz.com or by phone at 0711/17-99000 (Mo-Fr 10-12am & 13-15am).

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