Join Our Renowned Team for a Master Thesis on Deep Learning-Based Audio Analysis for Avian Population Estimation

At Fraunhofer Institute for Digital Media Technology IDMT, headquartered in Ilmenau, Germany, we leverage our internationally recognized expertise in areas such as applied electroacoustics, AI-based signal analysis, machine learning, data privacy, and security. Our research significantly impacts sectors like industrial and traffic monitoring, and media, contributing to advancements like automatic metadata extraction and audio manipulation detection.

The Semantic Music Technologies group is the focal point of pioneering research in extracting meaningful acoustic information. It combines audio signal processing and machine learning techniques aimed at addressing pressing real-world challenges.

Project Overview

This master thesis taps into a crucial ecological concern — counting bird populations in outdoor environments. The thesis will elaborate on deep learning methods tailored to decipher bird calls amidst noisy soundscapes, laying the groundwork for robust biometric measurements that contribute to biodiversity monitoring and conservation strategies.

Objective Breakdown

• Objective 1: Investigate bird song datasets annotated for polyphony or, alternatively, create a unique dataset from a mix of common bird species sound recordings, working alongside domain experts.
• Objective 2: Implement and assess deep learning models for bird counting, with a keen eye on differentiating individual and species-specific calls.
• Objective 3: Evaluate the models’ robustness under simulated environmental variations, ensuring the accuracy and reliability of the implemented methods in real-world scenarios.

Candidate Profile

We are looking for bright minds with a robust background in audio signal processing and deep learning. Proficiency in Python, TensorFlow or PyTorch, and a passion for bioacoustic research will be crucial. Your innovative approach could contribute significantly to both academic and practical domains through this thesis work.

Why Join Us?

Become a part of a dynamic team passionate about making a substantial impact on technology and society. We offer:

• Challenges and projects that invite innovation and forward-thinking.
• Extensive professional development and training opportunities.
• A supportive and diverse work environment ensconced in state-of-the-art facilities.
• Flexible working arrangements to ensure a commendable work-life balance.

We celebrate diversity and strongly encourage applications from all backgrounds. Let’s shape the future together!

Application Details

Interested candidates are advised to apply online. For additional information on the project specifics or the application process, please reach out:

Professional queries:
Dr. Jakob Abeßer

Application process inquiries:
Katrin Pursche

Apply by visiting
Requisition Number: 73723
Application Deadline: [Please insert deadline here]

We look forward to your application!