PhD Candidate for Optimal data interfaces for AI end-to-end radar data processing

We are CARIAD, the automotive software company of the Volkswagen Group. Our teams build automotive software platforms and digital customer functions for iconic brands like Audi, Volkswagen, and Porsche – supporting the Volkswagen Group in becoming the leading automotive technology company. With CARIDIANS in Germany, the USA, China, Estonia, and India, we are transforming automotive mobility for everyone.

Join us and be part of this exciting journey

YOUR TEAM

The aim of our PhD Program is to promote innovative topics that are relevant to CARIAD. We cooperate with top universities and bring new research projects to life. Our PhD candidates get the opportunity to create new innovations in their projects for CARIAD and the respective scientific field. All PhD projects are accompanied by a supervisor professor and a dedicated CARIAD mentor. Essential trainings for the PhD candidates complete the PhD Program.

Our ADAS & AD pre-development department develops an AI-based software stack for automated driving. Within the department, our team focuses on ADAS sensor sets, technology scouting, evaluating future sensor technologies through PoCs, and defining sensor KPIs. Based on new sensor technologies, we collect data and prepare datasets for our partner teams within the department to train new AI models. We are seeking a PhD candidate for the project "Optimal Data Interfaces for AI End-to-End Radar Data Processing".  In your daily work, you will work closely together with experts from all teams across the department alongside the ADAS/AD stack. We are an open-minded, highly motivated, and interdisciplinary team. We look forward to welcoming a self-motivated PhD candidate with an innovative spirit to join us.

WHAT YOU WILL DO

• PhD project with the working title: Optimal Data Interfaces for AI End-to-End Radar Data Processing
• Review of the state-of-the-art in the subject area
• Design of neural network architecture to handle radar data
• Comparison of different interfaces within the radar signal processing pipeline to choose the optimal input for the neural network
• Definition of evaluation criteria for different radar data representations
• Collection and recording of datasets based on real-life driving scenarios

WHO YOU ARE

• Master's degree in Computer Science, Electrical and Electronics Engineering, Information and Communication Systems, or equivalent
• Know-how of ADAS radar signal pre- and post-processing
• In-depth knowledge of machine learning algorithms and programming languages such as Python, C, or C++
• Experience with common machine learning frameworks like TensorFlow, PyTorch, etc.
• Working experience in real-world projects or internships relevant to the PhD topic
• Very good English language skills, both oral and written
• Knowledge of German is a plus 
• High level of commitment, goal-oriented, systematic way of working, and good networking skills

NICE TO KNOW

• Duration: 3 years
• Working with high ranked University
• Remote work options
• Possibility to supervise students
• Temporary work from abroad in selected countries
• 30 days paid leave
• Note: please upload your transcrip of records
• If you have further questions about the candidate journey at CARIAD, please contact us: .technology

At CARIAD, we embrace individuality and diversity because we believe our differences make us stronger. We actively seek to build teams with a variety of backgrounds, perspectives, and experiences. Our goal is to create an environment where everyone feels valued and empowered to contribute. If you need assistance with your application due to a disability, please reach out to us at .technology – we are happy to support you.