BACHELOR OR MASTER THESIS ON MACHINE LEARNING IN THE FIELD OF AUTONOMOUS FLYING IN INGOLSTADT
The Fraunhofer Application Center “Connected Mobility and Infrastructure” at Technische Hochschule – adversarial feature / data augmentation: Using adversarial augmentations to improve the
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 further fields of
technology in the areas of autonomous systems, digitization in traffic, highly automated flying, as well as
vehicle and traffic safety.
Our research team specializes in using machine learning and computer vision to transform the field of
highly automated flying systems. We provide a stimulating environment, as well as access to modern
facilities. We are searching for a highly motivated master’s/bachelor’s student to join our team and conduct
significant research in one or more of the areas listed below:
generalization, resilience, and adaptability of machine learning models
– multi-task learning: Developing a common backbone/feature extractor design that can accomplish
numerous tasks at once, such as object detection, scene parsing, depth estimation for autonomous
flying
– transfer learning / knowledge distillation: Investigating strategies for enhancing model efficiency by
transferring the knowledge gained from large models to smaller models that can be deployed under
real-world constraints
– panoptic segmentation: Fine tuning models for 2D / 3D panoptic segmentation based on camera
images / point cloud for autonomous flying
What you will do
– conduct literature study to identify research gaps and possibilities in the chosen research topic(s)
– design and implement algorithms, conduct tests, and gather data
– validate and refine research with team members and external partners
What you bring to the table
– enrolled in a Master’s or Bachelor’s program in computer science, electrical engineering, physics, computer science, mathematics, mechanical engineering or related fields
– prior research experience or coursework in machine learning, computer vision or robotics highly desirable
– proficiency in programming languages such as Python and experience with deep learning frameworks (e. g., PyTorch)
– passion for research and problem-solving
– excellent communication skills and ability to work collaboratively in a team
What you can expect
– opportunity to work in the field of machine learning and neural networks 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. and concepts in the fields of mobility, energy and security from forward-looking research to practical application. The institute cooperates closely with TU Dresden, TU Bergakademie Freiberg and TH Ingolstadt.
– access to state-of-the-art computational resources and modern infrastructure
– valuable research experience and exposure to real-world practical projects
– flexible working hours.
– potential for co-authorship on research papers and conference presentations
At its three locations Dresden, Ingolstadt and Berlin, Fraunhofer IVI’s researchers develop technologies
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:
Maximilian Otte
maximilian.otte@ivi.fraunhofer.de
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-00715
www.ivi.fraunhofer.de/en
Career Portal
Fraunhofer Institute for Transportation and Infrastructure Systems IVI
Requisition Number: IVI-Hiwi-00715 Application Deadline:
Job Segment:
Training, Computer Science, Electrical Engineering, Mechanical Engineer, Education, Technology, Engineering, Research