Aufgaben Mercedes-Benz, a pioneer in the automotive industry, is opening its doors to an ambitious intern eager to rethink the world of sound. We offer a unique opportunity to push the boundaries of what is possible and be part of a team shaping the future of vehicle acoustics
What We Offer:
It doesn't work completely without formalities. When sending your online application, please attach your CV, certificate of enrollment, current performance record, relevant certificates, if applicable proof of mandatory internship and the standard period of study (max. 5 MB) and mark your application documents as "relevant for this application" in the online form
Please find the criteria of employment "here"
Citizens of countries outside the European Trade Union please send, if applicable, your residence / work permit
We particularly welcome online applications from candidates with disabilities or similar impairments in direct response to this job advertisement. If you have any questions, you can contact the local disability officer once you have submitted your application form, who will gladly assist you in the onward application process: < email deleted for security reasons >
Please understand that we no longer accept paper applications and that there is no right to get your documents returned
If you have any questions regarding the application process, please contact HR Services by e-mail at < email deleted for security reasons > or by phone: 0711/17-99000 (Monday to Friday between 10 a.m. to 12 a.m. and 1 p.m. to 3 p.m.)
What We Offer:
- An internship followed by a master's thesis in a highly innovative environment
- The chance to work at the forefront of technological development and design groundbreaking audio solutions
- A creative and dynamic team that values innovation and originality
- Access to cutting-edge technologies and resources
- A culture that encourages critical thinking, curiosity, and the freedom to pursue extraordinary ideas
- Research and develop machine learning models for audio processing applications
- Investigate and implement deep neural networks to extract meaningful audio representations from visual data
- Work with state-of-the-art ML libraries and frameworks to build robust models
- Optimize and evaluate model performance for real-world applications
- Collaborate with an interdisciplinary team to integrate developed models into existing workflows
- Document findings, methodologies, and results for academic and technical reporting
- Currently pursuing a Master's degree in Informatics, computer Science, Electrical engineering, Data Science, audio communication or a related field.
- Strong background in machine learning and deep learning techniques
- Proficiency in Python and experience with ML libraries such as TensorFlow, PyTorch, or Keras.
- Familiarity with computer vision techniques and multimodal learning approaches
- Knowledge of acoustics and audio signal processing is a plus.
- Ability to work independently, think critically, and solve complex problems
- Strong analytical skills and experience with data-driven model evaluation
It doesn't work completely without formalities. When sending your online application, please attach your CV, certificate of enrollment, current performance record, relevant certificates, if applicable proof of mandatory internship and the standard period of study (max. 5 MB) and mark your application documents as "relevant for this application" in the online form
Please find the criteria of employment "here"
Citizens of countries outside the European Trade Union please send, if applicable, your residence / work permit
We particularly welcome online applications from candidates with disabilities or similar impairments in direct response to this job advertisement. If you have any questions, you can contact the local disability officer once you have submitted your application form, who will gladly assist you in the onward application process: < email deleted for security reasons >
Please understand that we no longer accept paper applications and that there is no right to get your documents returned
If you have any questions regarding the application process, please contact HR Services by e-mail at < email deleted for security reasons > or by phone: 0711/17-99000 (Monday to Friday between 10 a.m. to 12 a.m. and 1 p.m. to 3 p.m.)