PhD Student (f/m/d) Machine Learning / Artificial Intelligence and Computer Vision

Key Skills

Java Programming, Python Programming, C++, Framework, SQL, Machine learning techniques, Data science techniques, Deep Learning, Keras software library, PyTorch, TensorFlow, Fast.ai, Algorithms, Neural Networks

Job Description

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/artificial intelligence (AI). We are searching for talented students who bring in new ideas and help to develop our next generation of AI algorithms.

We are developing algorithms which, based on camera, lidar and radar sensor data, can understand complex driving scenarios (e.g. crowded multi-lane highways, inner cities), anticipate the behavior of other road users (e.g. pedestrian crossing the road, vehicle changing the lane or taking a turn) and finally make safe and comfortable driving decisions.

Are you (almost) finished with your Master's degree and want to pursue a PhD? Do you want to bridge the gap between academics and industry and apply your scientific expertise to real challenges in the area of automated and autonomous driving?

Your Tasks

• In general: Conduct research in topics related to machine learning/artificial intelligence and data science, consisting of e.g. algorithm development, data preparation and processing in Python, exploring neural network architectures, training neural networks, deployment of neural networks for real-time execution, visualization of results, generation of performance statistics etc.
• Example topic 1: Research and development of ML-based prediction system to achieve human-like traffic scene understanding and anticipation capability, to support various ADAS features or/and autonomous driving development.
• Example topic 2: Road model fusion based on camera-based lane recognition, vehicle detection and radar-based guard rail detection.
• Example topic 3: Depth estimation from mono camera images.

Your Profile

• You have a master’s degree in Electrical Engineering, Computer Science, Mathematics or similar
• You have a profound understanding of Deep Learning and / or Reinforcement Learning
• You have practical experience with at least one ML framework like Tensorflow, Keras, PyTorch, fast.ai etc.
• You are able to program self-reliant in C++ and Python.
• You have good English skills, German skills would be a plus.
• You are looking for a challenging task and like to be part of a team

We Offer

• Funding for a 3-year full-time PhD scholarship in cooperation with local universities
• The opportunity to work in a highly research-oriented environment that works on state-of-the-art machine learning solutions within the ADAS/AD domain
• Being part of a strong, supportive global team of highly educated machine learning engineers
• Hands-on work with real-world sensor data to develop and test your machine learning solutions
• Flexible and family-friendly working hours

Interested?

• Great! Please apply and include your CV and (important!) a grade overview.