Main Tasks: 1. RADAR Data Processing and Labeling: Process raw RADAR data and create accurate annotations. 2. ML-Based RADAR Object Classification: Train and fine-tune machine learning models for object classification using RADAR data. 3. Automated Ground Truth Labeling: Develop a pipeline to automate ground truth labeling by leveraging LiDAR point cloud data. 4. DL-Based RADAR Point Cloud Classification: Design, train, and fine-tune deep learning models for classifying RADAR point clouds. Profile requirements: 1. Enrolled as a Master’s student in Computer Science, Data Science, Artificial Intelligence, or a relevant field. 2. Basic understanding of machine learning concepts, demonstrated through the completion of at least one hands-on university course or online machine learning module. 3. Familiar with at least one deep learning framework, such as TensorFlow, PyTorch, or similar. 4. Proficient in Python programming. 5. Strong English reading and writing skills (able to document work in English and read academic papers). 6. Available for at least 3 days per week, with a minimum duration of 6 months.