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PhD Thesis: Data Analytics for Smart Grids

Job Description

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



Headed to the future? Hop right in.

Together with their customers Siemens works on making the Industry and Infrastructure more efficient, making clean energy more accessible and finding ways to make transport smart and eco-friendly.

As the leading Supplier for power transmission technology, control technology and grid planning we especially investigate how the transmission in the electric grids of the future can be carried out particularly efficiently. At the Siemens Research Center, we work in a network with various Siemens Business Units, with grid- and infrastructure operators, as well as leading academic institutes.

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

What part will you play?

  • Development of data-driven methods for the analysis and operation of power grids in the context of real customer projects

  • Selection of appropriate tools and methods for data analysis, (e.g., deep learning, Bayesian networks, reinforcement learning, clustering methods) to exploit existing and innovative data sources

  • Identification of relevant research questions in the field of data science for the adaptation and further development of the selected methods for tasks in the power grid area, e.g., the integration with physical grid models

  • Identification of relevant input data and suitable data sources, as well as definition of appropriate data models for their collection and processing (e.g., geodata, grid data, weather data)

  • Implementation and testing of all developments to evaluate the developed adaptations

  • If applicable, development and evaluation of new data-driven business models in the field of energy systems

  • Securing your work results through publications and invention disclosures.

We don’t need superheroes, just super minds.

  • You have a very successful university degree in computer science, mathematics, electrical or energy engineering or comparable academic qualification with a focus on numerical methods (optimization, algorithms, control/optimal control, statistical methods)

  • You have a sound knowledge of data analysis methods (e.g., deep learning, Bayesian networks, reinforcement learning, clustering) and ideally have already gained some experience with the implementation of such methods.

  • You are interested in working on relevant issues concerning the integration of physical models and business models in the field of energy systems and especially for the power sector

  • You can proactively develop topics and focal points in the course of your work and to further develop your topic in consultation with your supervisor.

  • You are familiar with a programming or scripting language (ideally Python and supplementary Java) and with collaborative software development tools (e.g., Gitlab).

  • You have a strong interest in developing practical solutions to challenging problems in the energy transition environment and taking them through to implementation

  • You have very good language skills in German and English

Make your mark in our exciting world at Siemens.


www.siemens.de
if you wish to find out more about the specific business before applying. 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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