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Master Thesis Reconfigurable Neural Networks for Dynamic Runtime Adjustments (f/m/x)

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Abschlussarbeit
Homeoffice: Nach Absprache

SOME IT WORKS. SOME CHANGES WHAT'S POSSIBLE.

SHARE YOUR PASSION.

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 Reconfigurable Neural Networks for Dynamic Runtime Adjustments.

In the evolving landscape of artificial intelligence, neural networks are increasingly deployed in dynamic environments where computational resources and performance requirements can vary significantly over time. Traditional neural networks, with their fixed architectures and static parameters, often fail to adapt efficiently to such changing conditions. Reconfigurable neural networks offer a promising solution by allowing dynamic adjustments to their architecture and parameters at runtime. This thesis aims to explore and develop reconfigurable neural network architectures that can adapt to varying computational constraints and performance requirements in real-time, ensuring optimal operation across diverse deployment scenarios.

What awaits you?

  • Research state-of-the-art reconfigurable architectures on embedded platforms for high efficiency under different conditions.
  • Gain practical AI experience by implementing a novel reconfiguration method, 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

  Anstellungsart
Abschlussarbeit
  Homeoffice
Nach Absprache

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