Research Associate (m/f/d), EG 14 TV-H
Core
Develop machine learning methods for perceiving cyclists' behavior using vehicle sensor data (camera, LiDAR) and cross-labelling approaches for automated annotation within the DyNaMo project.
Role type
Research Associate (PI-track)
Builds
Perception algorithms for autonomous driving and data analysis methods
Domain
Automotive (autonomous driving) + Machine Learning
Deliverable
production ML models
Required skills
Computer vision, deep learning, data analysis, Python, PyTorch, TensorFlow, scikit-learn, Pandas, OpenCV, NumPy, external fundraising, team leadership
Preferred skills
Project management, supervising PhD students
Technologies
Slurm-based compute cluster, test vehicle with camera/LiDAR/radar
Responsibilities
Designing and conducting measurement campaigns (lab and field), integrating multi-modal model information, contributing to group tasks, leading a small team
Seniority
Senior, hands-on IC with team leadership
