Mercedes-Benz AG | Germany | Sindelfingen | Full time / Home office | Published since: 14.04.2025 on stepstone.de
PhD in the field of Adaptive Multi-Modal Fusion in cooperation with a university from August 2025
Life is always about becoming... In life it is about going on a journey to become the best version of our future self. As we discover new things, we face challenges, master them and grow beyond us.
Apply to Mercedes-Benz and find the area where you can develop your talents individually. You will be supported by visionary colleagues who share your pioneering spirit. Joining us means becoming part of a global team whose goal is to build the most desirable cars in the world. Together for excellence.
Number: MER0003M64 JOBV1_EN
* After clicking the 'Read more' button, the original advert will open on our partner's website, where you can see the details of this vacancy and contact information. If you need a translation of this text, after returning to our website it will be prepared and you can read it by clicking the 'Translation' button.
Life is always about becoming... In life it is about going on a journey to become the best version of our future self. As we discover new things, we face challenges, master them and grow beyond us.
Apply to Mercedes-Benz and find the area where you can develop your talents individually. You will be supported by visionary colleagues who share your pioneering spirit. Joining us means becoming part of a global team whose goal is to build the most desirable cars in the world. Together for excellence.
Number: MER0003M64 Mercedes-Benz Group AG is one of the most successful automotive companies in the world. With Mercedes-Benz AG, the vehicle manufacturer is one of the largest providers of premium and luxury cars and vans. We shape the future of mobility at Mercedes-Benz by developing autonomous and automated driving systems for motorways and urban areas. Our teams are inspired by current trends, find the best solutions for our customers and develop the latest and best core technologies to meet these challenges. Be part of an agile, innovative team that is passionate about making our vehicles safer and more independent. We are looking for a talented, active and committed PhD student who, within our Sensor Fusion Team in the area of Böblingen, researches and actively drives the technologies of tomorrow. These challenges include: You provide basic insights for our sensor Perception & Fusion System of the future. This stack, based on camera, lidar and radar data, forms the basis for the environmental model, which describes other road users and infrastructure information You explore new, data-driven multi-sensor perception & fusion algorithms and architectures using Transformer-based approaches to achieving the best possible driving behavior You will be practicing current research in Sensor Perception & Fusion, publishing your own contributions and presenting them at conferences You collect your results in reports and present them regularly in the Sensor Perception & Fusion Teams Adjustment requirement is the support of the doctoral project by a university lecturer. The selection of a corresponding person is the responsibility of the doctoral student.
Ideally, you bring the following: Complete master studies with excellent results in engineering, such as computer science, robotics, physics or a related field Very good knowledge of state-of-the-art machine learning, such as transformer and attention concepts Good knowledge of probabilisticly motivated sensor fusion algorithms Experience with the application of named concepts on Object Perception and Tracking, based on multimodal sensor data such as radar, lidar and camera Very good programming knowledge in Python Practical experience with Docker, Conda, Pytorch and ML frameworks like MMDetection C++ Programming skills are advantageous English language skills Personal competencies: High level of discipline, initiative, self-employment and commitment Excellent communication and team skills as part of a global team in a multicultural environment Ability to identify existing problems and methodological, creative approach to solution design Great willingness to learn and pass on knowledge, for example in the care of students Openness to question the state of the art and high motivation to deepen a topic Additional information: Do you want to make your promotion in cooperation with Mercedes-Benz Group AG? We offer you an international network of experts, research materials, work insights and personal mentors that will assist you as a contact person in addition to your faculty. PhD at a renowned university with the support of Mercedes-Benz Group AG as a non-academic partner – and use the know-how of a globally active group. Please apply exclusively online and mark your application documents as ''relevant for this application' in the online form. You can find information about the setting criteria here. Members of countries outside the European Economic Area may send their residence/work permit. We are particularly pleased to receive applications for disabled people and disabled people. At SBV-Sindelfingen@mercedes-benz.com you can also contact the site's heavy-handed representative, who will be happy to support you in the further application process. Questions about the application process will be answered by HR Services by e-mail to myhrservice@mercedes-benz.com or by phone: 0711/17-99000 (Monday to Friday between 10-12 am and 13-15 pm)
Food supplements Employee handy possible Employee discounts possible Employee participation possible Staff Events Coaching Flexible working time possible Hybrid work possible Health measures Employment Mobility offers JOBV1_EN
Company location
Location
![]() | Mercedes-Benz AG | |
Sindelfingen | ||
Germany |
The text of this ad was translated from German into English using an automatic translation system and may contain semantic and lexical errors. Therefore, it should be used for introductory purposes only. For more detailed information, see the original text of the ad at the link below.
For more information read the original ad