Master Thesis On Inference Optimization For Neural Networks In Ingolstadt

The Fraunhofer Application Center “Connected Mobility and Infrastructure” at 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 further fields of
technology in the areas of autonomous systems, digitization in traffic, highly automated flying, as well as
vehicle and traffic safety.

We are currently seeking exceptional candidates to undertake their Master’s thesis focusing on developing
innovative techniques to enhance the efficiency and performance of neural network inference. From image
identification to natural language processing, neural networks have transformed a wide range of
applications. However, the computing requirements of using these networks in real-time applications pose
present challenges. Your research will concentrate on exploring methods that accelerate and streamline
neural network inference, allowing them to run efficiently in resource-constrained environments while
maintaining high accuracy.

What you will do

– research and analyze cutting-edge inference optimization methods for neural networks
– design, implement, and experiment with innovative approaches to enhance inference speed and efficiency
– collaborate with research team to validate proposed methods on various real-world use cases

What you bring to the table

– enrolled in a Master’s program in computer science, electrical engineering, physics, mathematics, mechanical engineering or related fields
– strong background in machine learning and deep learning
– proficiency in programming languages such as Python and experience with deep learning frameworks (e. g., TensorFlow, PyTorch)
– knowledge in inference optimization techniques and frameworks (e. g., TensorRT)
– 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
– 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

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.

At its three locations Dresden, Ingolstadt and Berlin, Fraunhofer IVI’s researchers develop technologies

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.

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

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-00717

www.ivi.fraunhofer.de/en

Career Portal

Fraunhofer Institute for Transportation and Infrastructure Systems IVI 

www.ivi.fraunhofer.de 

Requisition Number: IVI-Hiwi-00717              Application Deadline: