3 data warehouse jobs found in Stuttgart

Area of ​​activity: Research & Development incl. Design Department: Device Integration Company: Mercedes-Benz AG Location: Mercedes-Benz plant Sindelfingen, Sindelfingen Start date: November 16, 2026 Publication date: September 30, 2026 Job number: MER00048W1 Working hours: Part-time Tasks In our department Infotainment Device Integration, we are responsible for the seamless integration of consumer devices such as smartphones, headphones, and wearables into the vehicle infotainment system. This includes the development, validation, and continuous improvement of technologies such as Bluetooth, Apple CarPlay, and Google Android Auto. We are looking for you as a Working Student Data Analytics for Infotainment Systems for this exciting and challenging area. You will master these tasks: Analyze quality, usage, and diagnostic data from customer vehicles in the field Identify product...

Faculty of Medicine, Radiology, RACOON Research Infrastructure, Ref. No. 7931 Full-time: 100% Temporary contract: 1 year 1 Start date: as soon as possible Application deadline: October 6, 2026 TV UK i.d.R. E13 2 Tasks Coordination of organizational and scientific processes in close collaboration with the project management Advising project partners on study design, data management and data integration Organization and support of external audits (business trips) Support in the further development and implementation of the technical research infrastructure Contributing to the preparation of scientific publications, project reports and grant applications. Profile Completed university degree in (medical) informatics, bioinformatics, data science, medical physics or a comparable field Experience in database management and with research infrastructures is required (e.g., federated systems, clinical data...

Tasks Are you eager to connect physical insights with advanced AI? We are offering an exciting master's thesis opportunity to work on physically informed machine learning for system identification and performance modeling of MEMS gyroscopes. During your assignment, you will construct machine learning (ML) algorithms for system identification and performance prediction of MEMS gyroscopes. You will examine MEMS gyroscope data through detailed analysis. Furthermore, you will assess physically informed ML in comparison to other architectures. Furthermore, you will acquire a deep physical understanding of MEMS gyroscopes to optimize your models. Finally, you will work with real-world sensor data to validate your findings. profile Education:   Master studies in the field of   Informatics, Physics, Engineering or comparable with good grades Experience and Knowledge:   in data driven parameter identification; knowledge of Python,...