PhD Thesis Scalable and explainable End2End Driving Model (SEED)
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Monthly Salary:
Posted on:
9 hours ago
Vacancies:
1 Vacancy
Job Summary
Automated driving is one of the most significant technological challenges of our time. While traditional autonomous systems rely on modular pipelines the industry is shifting toward end-to-end learning - a paradigm that scales massively but often acts as a black box. We are seeking an excellent PhD candidate to bridge this gap. Your goal is to be the architect of a next-generation modular and scalable end-to-end driving model. You will explore how to join the benefits of two competing paradigms: the data-driven power of unified models and the safety-critical explainability of decomposed pipelines. This position offers a unique bridge between academic excellence and industrial application: alongside publishing your research at top-tier venues you will have the opportunity to see your contributions integrated into the next generation of real-world ADAS products.
Your contribution to the future of driving:
- Master the State-of-the-Art: As part of your role you conduct a deep-dive analysis of current breakthroughs in end-to-end autonomous driving. You will investigate how to exploit large-scale datasets without relying on labeled data for every sub-task identifying the next frontier of innovation.
- Innovate and Develop: Furthermore you will design and implement novel deep neural network architectures that prioritize both high-performance scaling and human-interpretable explainability.
- Experiment and Validate: Through rigorous experiments on public benchmarks and our massive Bosch-owned autonomous driving datasets you will validate the performance and reliability of your models.
- From Lab to Road: In close collaboration with expert project teams in deep learning and computer vision you will brainstorm new ideas and have the unique opportunity to deploy your software on hardware validating your research on real automotive driving systems.
- Share Your Success: We support your academic growth. You will publish your findings and research outcomes at top-tier computer vision and machine learning journals and conferences.
Qualifications :
- Education: Master degree in Electrical Engineering Computer Science or similar with excellent grades
- Experience and Knowledge: detailed knowledge on computer vision 3D vision machine learning deep learning artificial intelligence (Transformer Sparse and BEV Queries) and experience with dedicated development tools (TensorFlow PyTorch Python)
- Personality and Working Practice: you show high level of enthusiasm; you are creative and work independent with excellent task-management; team spirit assertiveness and persuasiveness are your strong characteristics
- Enthusiasm: interest in conceptual work and method-based design
- Languages: fluent in English and German written and spoken
Additional Information :
final topic depends on your university.
Start: by prior agreement
Please submit all relevant documents (CV certificates and links to GitHub or kaggle account).
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.
Need support during your application
Sarah Schneck (Human Resources)
49 81
Need further information about the job
Joel Janai (Functional Department)
49 6
Work #LikeABosch starts here: Apply now!
Remote Work :
No
Employment Type :
Full-time
Key Skills
- Python
- C/C++
- Fortran
- R
- Data Mining
- Matlab
- Data Modeling
- Laboratory Techniques
- MongoDB
- SAS
- Systems Analysis
- Dancing
About Company
Bosch first started in Vietnam with a representative office in 1994. Bosch has its main office in Ho Chi Minh City, with branch offices in Hanoi and Da Nang, and a Powertrain Solutions plant in the Dong Nai province to manufacture pushbelt for continuously variable transmissions (CVT) ... View more
