Master Thesis Efficient Deployment of Vision Transformer Models (f/m/x)
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More than 90% of automotive innovations are based on electronics and software. That's why creative freedom and lateral thinking are so important in the pursuit of truly novel solutions. That’s why our experts will treat you as part of the team from day one, encourage you to bring your own ideas to the table – and give you the opportunity to really show what you can do.
We, the BMW Group, offer you an interesting and varied Master thesis in the area of Efficient Deployment of Vision Transformer Models.
In recent years, vision transformer (ViT) architectures have emerged as the state-of-the-art in vision tasks, outperforming traditional convolutional neural networks (CNNs) in areas such as classification and semantic segmentation. Despite their superior performance, ViT models are often computationally intensive and resource-hungry, posing significant challenges for deployment on edge devices with limited compute and memory resources. Efficient deployment strategies are therefore essential to leverage the full potential of ViTs in real-world applications where resource constraints are prevalent. This thesis focuses on developing and optimizing methods for the efficient deployment of vision transformer models on edge devices, ensuring high performance while minimizing computational and memory overheads.
What awaits you?
- Research state-of-the-art efficient deployment of Vision Transformer models on embedded platforms.
- Gain practical AI experience by implementing a novel efficient deployment strategy, contributing to our PyTorch based research stack.
- Utilize our cutting-edge training infrastructure and platforms to conduct experiments and evaluate your approach efficiently.
- Present the thesis results using the scientific method, both in written and oral formats.
- Collaborate with an experienced team that has published at international peer-reviewed conferences.
- Engage with an international and diverse team of doctoral candidates and students at the Autonomous Driving Campus in Unterschleißheim.
Please note that you must ensure that the thesis is supervised by a university.
What should you bring along?
- You are a master student approaching the end of your degree in computer science or related fields with focus on machine learning or artificial intelligence.
- You have strong knowledge in computer vision concepts, tasks and Vision Transformers.
- You have excellent programming skills in Python, PyTorch and worked with modern programming environment tools such as Docker and Git.
- You speak English fluently.
- You are driven by curiosity and motivated to solve problems independently as well as sharing ideas and working in a team.
What do we offer?
- Comprehensive mentoring & onboarding.
- Personal & professional development.
- Flexible working hours.
- Digital offers & mobile working.
- Attractive remuneration.
- Apartment offers for students (subject to availability & only Munich).
- And many other benefits - see bmw.jobs/benefits
You are enthused by new technologies and an innovative environment? Apply now!
At the BMW Group, we see diversity and inclusion in all its dimensions as a strength for our teams. Equal opportunities are a particular concern for us, and the equal treatment of applicants and employees is a fundamental principle of our corporate policy. That is why our recruiting decisions are also based on personality, experience and skills.
Find out more about diversity at the BMW Group at bmwgroup.jobs/diversity
Earliest starting date: from 10/01/2024
Duration: 6 months
Working hours: Full-time
Contact:
BMW Group HR Team
+49 89 382-17001
