Bosch Group
Master Thesis Automated Driving Systems(m/w/x)
Full-timeOn-siteNot specified
Renningen
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BOBosch Group
PhD Thesis - Scalable and explainable End2End Driving Model (SEED)(m/w/x)
Leonberg
Full-timeOn-site
AI/ML
Data Science
Nejo AI Summary
Researching and developing novel deep neural network architectures for autonomous driving systems at a global technology supplier. Master's degree in Electrical Engineering/Computer Science and detailed knowledge of computer vision, 3D vision, machine learning required. Dedicated academic growth support.
Requirements
- Master degree in Electrical Engineering, Computer Science or similar
- Excellent grades
- Detailed knowledge of computer vision
- Detailed knowledge of 3D vision
- Detailed knowledge of machine learning
- Detailed knowledge of deep learning
- Detailed knowledge of artificial intelligence (Transformer, Sparse and BEV Queries)
- Experience with dedicated development tools
- High enthusiasm
- Creativity
- Independent work ability
- Excellent task management
- Team spirit
- Assertiveness
- Persuasiveness
- Interest in conceptual work
- Interest in method-based design
- Fluent English (written and spoken)
- Fluent German (written and spoken)
Tasks
- Conduct deep-dive analysis of end-to-end driving breakthroughs
- Investigate exploiting large-scale datasets
- Identify next frontiers of innovation
- Design novel deep neural network architectures
- Implement novel deep neural network architectures
- Conduct rigorous experiments on public benchmarks
- Conduct rigorous experiments on Bosch datasets
- Validate model performance and reliability
- Collaborate with deep learning project teams
- Brainstorm new ideas
- Deploy software on hardware
- Validate research on automotive driving systems
- Publish research in top-tier venues
Education
- Master's degree
Languages
- English – Business Fluent
- German – Business Fluent
Tools & Technologies
- TensorFlow
- PyTorch
- Python
- Transformer
- Sparse Queries
- BEV Queries
Benefits
Mentorship & Coaching
- Academic growth support
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Bosch Group and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Not a perfect match?
- Bosch Group
Master Thesis Advanced Control Strategies for Next-Generation Vehicle Dynamics(m/w/x)
Full-timeInternshipOn-siteRenningen - Fraunhofer-Gesellschaft
Master Thesis - Multi-modal traversability estimation for Autonomous Outdoor Navigation(m/w/x)
Full-timeInternshipOn-siteStuttgart - Fraunhofer-Gesellschaft
Master Thesis - Reinforcement Learning for wheeled, bipedal robots(m/w/x)
Full-timeInternshipOn-siteStuttgart - Bosch Group
PhD – Generative Models for Closed-loop Synthesis(m/w/x)
Full-timeWorking StudentOn-siteRenningen
BOBosch Group
PhD Thesis - Scalable and explainable End2End Driving Model (SEED)(m/w/x)
Leonberg
Full-timeOn-site
AI/ML
Data Science
Nejo AI Summary
Researching and developing novel deep neural network architectures for autonomous driving systems at a global technology supplier. Master's degree in Electrical Engineering/Computer Science and detailed knowledge of computer vision, 3D vision, machine learning required. Dedicated academic growth support.
Requirements
- Master degree in Electrical Engineering, Computer Science or similar
- Excellent grades
- Detailed knowledge of computer vision
- Detailed knowledge of 3D vision
- Detailed knowledge of machine learning
- Detailed knowledge of deep learning
- Detailed knowledge of artificial intelligence (Transformer, Sparse and BEV Queries)
- Experience with dedicated development tools
- High enthusiasm
- Creativity
- Independent work ability
- Excellent task management
- Team spirit
- Assertiveness
- Persuasiveness
- Interest in conceptual work
- Interest in method-based design
- Fluent English (written and spoken)
- Fluent German (written and spoken)
Tasks
- Conduct deep-dive analysis of end-to-end driving breakthroughs
- Investigate exploiting large-scale datasets
- Identify next frontiers of innovation
- Design novel deep neural network architectures
- Implement novel deep neural network architectures
- Conduct rigorous experiments on public benchmarks
- Conduct rigorous experiments on Bosch datasets
- Validate model performance and reliability
- Collaborate with deep learning project teams
- Brainstorm new ideas
- Deploy software on hardware
- Validate research on automotive driving systems
- Publish research in top-tier venues
Education
- Master's degree
Languages
- English – Business Fluent
- German – Business Fluent
Tools & Technologies
- TensorFlow
- PyTorch
- Python
- Transformer
- Sparse Queries
- BEV Queries
Benefits
Mentorship & Coaching
- Academic growth support
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Bosch Group and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
About the Company
Bosch Group
Industry
Engineering
Description
Das Unternehmen entwickelt hochwertige Technologien und Dienstleistungen, die das Leben der Menschen verbessern.
Not a perfect match?
- Bosch Group
Master Thesis Automated Driving Systems(m/w/x)
Full-timeOn-siteNot specifiedRenningen - Bosch Group
Master Thesis Advanced Control Strategies for Next-Generation Vehicle Dynamics(m/w/x)
Full-timeInternshipOn-siteRenningen - Fraunhofer-Gesellschaft
Master Thesis - Multi-modal traversability estimation for Autonomous Outdoor Navigation(m/w/x)
Full-timeInternshipOn-siteStuttgart - Fraunhofer-Gesellschaft
Master Thesis - Reinforcement Learning for wheeled, bipedal robots(m/w/x)
Full-timeInternshipOn-siteStuttgart - Bosch Group
PhD – Generative Models for Closed-loop Synthesis(m/w/x)
Full-timeWorking StudentOn-siteRenningen