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PhD Thesis: Data-driven operational strategies for autonomous distribution grids

Job Description

Mode of Employment: Limited, Part-time 17,5 h/week



Headed to the future? Hop right in.

We are passionate about innovations that mean real progress. We are excited about technologies that still need to be developed. What about you? Do you want to use your curiosity, passion, and creativity to make the lives of millions of people easier and better? We are looking for talented individuals who turn dreams into reality! We know that refreshing concepts only come from fresh ways of thinking. And unusual ideas are only born of an extraordinary environment. In other words, join Siemens as a graduate – by beginning your career with us. We’re looking forward to seeing your perspective.

What part will you play?

As part of your PhD thesis, you will research over a period of 3 years how minimal system data from different sources and modern methods of AI and optimization can be used to improve grid operations - to make the energy transition technically possible and economically attractive. At Siemens Technology, we offer you an excellent environment to apply research on fundamental questions in the context of real customer projects.

  • You develop data-driven, parameterization-free methods for monitoring and operating power grids in the context of real customer projects.
  • You identify relevant research topics in machine learning and mathematical optimization for the adaptation and further development of the selected methods for tasks in the power grid area, e.g., by integrating physical grid models.
  • Additionally, you evaluate and develop suitable methods for state estimation and control, e.g., deep learning, reinforcement learning, optimization.
  • You analyze real systems and measurement data with focus on the applicability of the developed methods.
  • Securing the results of your work through publications and patent applications is also part of your job.

We don’t need superheroes, just super minds.

  • You have a very successful university degree in computer science, mathematics, physics, electrical or power engineering or have a comparable academic qualification with a focus on algorithmic methods.
  • You have a solid knowledge of machine learning and mathematical optimization methods, e.g., reinforcement learning, nonlinear optimization, optimal control, and ideally have already gained some experience with the implementation of corresponding methods.
  • Furthermore, you can proactively develop topics in the course of your work and further develop your thesis in consultation with your supervisor.
  • The confident handling of a programming or scripting language, ideally Python, and of collaborative software development tools, e.g., Gitlab, is a must for you.
  • In addition, you have a strong interest in developing practical solutions to challenging problems in the energy transition environment and bringing them to implementation.
  • Very good written and oral English skills are required; German skills would be an asset.

Make your mark in our exciting world at Siemens.


www.siemens.de
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Do you have questions about the application? Here you will find answers to frequently asked questions.

If you have more questions, please contact: www.siemens.de/fragenzurbewerbung

www.siemens.com/careers
if you would like to find out more about jobs & careers at Siemens.

As an equal-opportunity employer we are happy to consider applications from individuals with disabilities.


Organization: Technology

Company: Siemens AG

Experience Level: Early Professional

Job Type: Part-time

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