Thesis in Multi-Modal Predictions for End-to-End Architectures

Thesis in Multi-Modal Predictions for End-to-End Architectures

• Full-time

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In autonomous driving, accurate predictions are crucial for safety and efficiency. Predicting the future movements of surrounding objects and vehicles enables systems to plan proactively, reduce accidents, and improve driving experience. Feedback from predictions to perception allows continuous learning and improvement of end-to-end capabilities, enhancing decision-making in dynamic environments.

During your thesis, you will address the need for predictions in autonomous driving systems, aiming to improve the coupling between predictions and perception (multi-object detection and tracking).

Query-based approaches have gained attention for their performance and integration ease within end-to-end architectures. Currently, architectures struggle with information flow from downstream tasks to perception models. This thesis will explore methods to enhance this, considering multi-modal prediction models.

• Education: Studies in Computer Science or a comparable field.
• Experience and Knowledge: Data analysis and visualization; proficiency in Python and tools like Pandas, NumPy, and Matplotlib; knowledge of deep learning frameworks; familiarity with TensorFlow, Keras, or PyTorch; understanding of computer vision; experience with OpenCV or similar libraries; familiarity with autonomous systems (e.g., automated driving).
• Personality and Working Practice: Eager to learn, capable of tackling complex challenges, developing innovative solutions, and articulating technical concepts clearly to both technical and non-technical audiences.

Start: According to prior agreement
Duration: 6 months

Requirements: Enrollment at university. Please attach your CV, transcript of records, examination regulations, and, if applicable, a valid work and residence permit.

If you are nearing the completion of your Bachelor's degree and wish to gain practical experience before pursuing a Master's, our PreMaster Program might be perfect for you! Check our vacancies here.

Diversity and inclusion are core to our culture. We welcome applications from all genders, ages, disabilities, religions, ethnicities, and sexual orientations.

Need more information?
Joerg Wagner (Functional Department)
+49 711 811 35050