Ph.D. Student Radar Machine Learning / Artificial Intelligence (f/m/d)
Ph.D. Scholarship Radar Machine Learning / Artificial Intelligence
APTIV is one of the largest automotive suppliers and a global technology leader, with more than 190,000 people worldwide.
We address mobility’s toughest challenges and deliver market-relevant solutions for our customers. One key technology for further pushing the boundaries of advanced driver assistance systems and autonomous driving is machine learning and artificial intelligence.
Radar has been considered a measurement device for a long time without machine learning playing a major role in its signal processing.
But with more modern radar sensors and in more complex environments, machine learning can bring an important value add to the interpretation of the environment.
This work will investigate new methods to improve radar perception for different applications using machine learning to enable to the development of next generation radar machine learning perception.
Your Profile
You hold a master’s degree in Computer Science, Engineering, Math, Physics or similar
Good knowledge in programming languages like Python or C++
Good grades and a good understanding of mathematical and physical theoretical concepts
Good communication skills (written and spoken) in English
You bring self-motivation, hands-on spirit and enjoy working on challenging tasks
Good time management and self-reliance
Why join us?
You can grow at Aptiv. Aptiv provides an inclusive work environment where all individuals can grow and develop, regardless of gender, ethnicity or beliefs
You can have an impact. Safety is a core Aptiv value; we want a safer world for us and our children, one with : Zero fatalities, Zero injuries, Zero accidents
You have support. We ensure you have the resources and support you need to take care of your family and your physical and mental health with a competitive health insurance package
We Offer
Funding for a 3-year full-time Ph.D. scholarship in cooperation with a university
Opportunity to work on state-of-the-art machine learning solutions in a research-oriented environment
Hands-on work with real-world data
A strong global team of highly educated machine learning engineers to contribute and support you
Interested?
Great! Please apply and include your CV and (important!) a grade overview.
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