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Advanced Development/Research Munich 18.05.2022

PhD candidate in the area of quantum computing enhanced generative adversarial networks (f/m/d)

THE FUTURE IS WHAT WE CREATE WHEN WE TAKE OUR VISIONS TO THE LIMITS.

PHD AT THE BMW GROUP.

Bridging the gap between your doctoral studies and the kind of career challenge you’re looking for isn’t always easy. That’s why our ProMotion PhD programme gives you the opportunity to apply your passion and scientific expertise to very real challenges that could shape the future of mobility. If selected, you’ll have the chance to really develop your own future career path with us through your practice-related thesis, promote your chosen specialty from within – and position yourself to secure the career you’ve always wanted.

Description

We, the BMW Group, offer you an interesting promotion in the area of quantum computing enhanced generative adversarial networks.

 

The success of the BMW Group is founded on long-term thinking and responsible action. Being among the first-movers, BMW Group has set the evolution course on sustainability and efficient resource management. Often, traditional approaches to design of vehicle components and the corresponding construction methods are exhausted. Hence, new generative modeling approaches are being investigated to enhance the development process, reduce the production time and resources while improving the product quality and customers experience. Employing AI solutions and tools such as Generative Adversarial Networks (GANs) enables engineers to create lighter, safer, and more sustainable automotive components by:

•             reducing mass while maintaining performance standards, meeting design goals and respecting constraints

•             improving and optimizing durability of vehicle components, removing the weakness area

•             creating the optimal thermal design for heat transmission between battery cells and other applications

•             reducing assembly cost of complex automotive components into the solid part, optimizing the supply chain

Besides all the advantages, classical GANs have some common drawbacks such as non-convergence, the mode collapse or diminished gradients, that became an area of active research. Recently, there has been significant progress in the development of quantum GANs proven efficient in image and video generation, materials discovery. Using Quantum Computing to create new viable, fast and robust realizations of qGANs will allow a better understanding of a Generative Design process, making it more efficient and creative.

 

The research project will focus on the development and evaluation of the robust Quantum Computing realizations of Generative Adversarial Networks in application to Generative Design of vehicle components.  It will be integrated into the activities of the BMW Group “AI-based Vehicle Functions & Network AI” department and supported by the field experts working on the topics of Generative Design, autonomous driving, and crashworthiness simulations. The PhD candidate will be based at BMW Group's Research & Technology House in Garching, Germany, including the possibility of travelling and on-site working with academic supervisors.

 

What awaits you?

Together with the experts from BMW Group and academic advisors the PhD candidate will work on:

•             Identification, evaluation and analysis of potential advantages and sensible use-cases of for generative modeling on NISQ and FT devices.

•             In-depth analysis of available classical Deep Learning approaches for generative modeling and design.

•             In-depth analysis of existing quantum and hybrid quantum - classical realizations of GANs.

•             Development of a quantum computing enhanced GANs, numerical validation, benchmarking, applicability to BMW Group’s specific use-cases and scenarios.

 

 

What should you bring along?

•             Solid background in one of the fields: Machine Learning, Generative Modeling and Design, Quantum Computing.

•             A degree qualifying for academic PhD research in a relevant field of computer science, mathematics, physics, engineering, or similar.

•             Experience with development of Quantum Computing algorithms and applications.

•             Strong programming skills.

•             Curiosity and persistence.

 

 

Are you enthused by new technologies and an innovative environment? Apply now!


 

Earliest starting date: 07/01/2022

Duration: 36 months.
Working hours: Full-time


Contact:
BMW Group Recruiting Team
+49 89 382-17001

 

PhD candidate in the area of quantum computing enhanced generative adversarial networks (f/m/d)

20220518
Automotive
Munich
Germany
Legal Entity:
BMW AG
BMW Group
Location:
Munich
Job Field:
Advanced Development/Research
Job Id:
61410
Publication Date:
18.05.2022
FullTime
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