Für Stelle bewerben

This master's thesis research challenge involves developing automated methods for detecting noise events (e.g., vehicle sounds, glass breakage, animal noises) using acoustic data. The focus is on semi-supervised learning, incremental learning, or few-shot learning techniques, aiming to leverage large unlabeled datasets and efficient methods for model training. The project focuses on vehicle-related sound detection and classification.

Requirements

• Ongoing studies in computer science, mechatronics, electrical engineering or a comparable technical or natural science field
• Programmer experience in at least one higher programming language
• Very good English language skills in both written and spoken form
• Willingness to learn, high initiative and teamwork skills

Benefits

• Full integration and within school-collaboration with IAV experts
• Attractive remuneration after our cover tariff