MASTER THESIS MONOCULAR DEPTH ESTIMATION FOR AUTONOMOUS DRONES USING DEEP LEARNING & COMPUTER VISION

The Fraunhofer-Gesellschaft (www.fraunhofer.com) currently operates 76 institutes and research institutions throughout Germany and is the world’s leading applied research organization. Around 30 800 employees work with an annual research budget of 3.0 billion euros.

The Fraunhofer Application Center »Connected Mobility and Infrastructure« at the Technische Hochschule Ingolstadt (THI) focuses on current and future topics of automated and cooperative driving. Diverse competences in the fields of sensor technology, communication and artificial intelligence are combined, fostering synergies with the local industry and aiming for close cooperation with the city of Ingolstadt and its partners. With research on urban air mobility, the application center is opening up further fields of technology in the areas of autonomous systems, digitization in traffic, and vehicle and traffic safety.

What you will do

For our current projects we are looking for excellent students who would like to write their thesis in the area of Computer Vision and Deep Learning. The thesis(es) will develop cutting-edge methods for monocular depth estimation, which will be applied in the environment perception of autonomous drones.

What you bring to the table

student of Computer or Data Science, Mathematics, Physics, Electrical and Information Engineering or similar
strong background in the areas of Deep Learning and Computer Vision
excellent academic performance
very good programming skills in Python
experience with frameworks like PyTorch and/or TensorFlow
own work in the field of Computer Vision
deep understanding of neural networks and transformer architectures
structured, self-dependent and result-oriented way of working
ambition, creativity and commitment in the daily work routine
high motivation and ability to work in a team

What you can expect

challenging tasks in cutting-edge and application-relevant subject areas
interdisciplinary research on promising technologies
professional supervision
adequate remuneration
a modern research infrastructure
flexible working hours
a young, dynamic team in an open and friendly working environment

Fraunhofer is Europe’s largest application-oriented research organization. Our research efforts are geared entirely to people’s needs: health, security, communication, energy and the environment. We are creative. We shape technology. We design products. We improve methods and techniques. We open up new vistas.

The Fraunhofer Institute for Transportation and Infrastructure Systems IVI in Dresden employs more than 150 research fellows in five departments and collaborates closely with the TU Dresden, the TU Bergakademie Freiberg and the Technische Hochschule Ingolstadt.

We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability.

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.

Interested? Apply online now. We look forward to getting to know you!

If you have any questions, please contact:

Markus Gross
markus.gross@ivi.fraunhofer.de
Phone +49 (0) 152 02830347

Fraunhofer Application Center »Connected Mobility and Infrastructure«

Visiting address
Stauffenbergstraße 2a
85051 Ingolstadt

Postal address
Technische Hochschule Ingolstadt
Esplanade 10
85049 Ingolstadt

Please state the requisition number: IVI-Hiwi-00699

Fraunhofer Institute for Transportation and Infrastructure Systems IVI

www.ivi.fraunhofer.de

Requisition Number: IVI-Hiwi-00699 Application Deadline:

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