Mode of Employment: Limited; 20 hours/week Develop what will be important tomorrow. Do you like the sound of finding the smartest solution side by side with professionals and experts? If so, complete your PhD thesis with us. We can help you to combine knowledge, discover connections, and formulate ideas. When you join our team, you will gain an insight into a range of departments and processes. It is a chance like no other to break new ground as we head into the future of electrification, automation, and digitalization. Seize this opportunity today Change the future with us. The increasing use of volatile renewable energies, electric vehicles, heat pumps and energy storages raises the complexity and uncertainty in the operation of our electrical infrastructure. This shift underscores the need for accurate and robust time-series forecasting, anomaly detection and system identification to effectively manage energy systems. In this context, foundational models, including advanced AI techniques like Large Language Models (LLMs), are rapidly being adapted to enhance these critical tasks. These foundational models hold the potential to revolutionize the management of energy systems by providing deeper insights and improving operational accuracy without high engineering effort. Exploration and identification of scenarios for utilizing these models is essential, involving a comprehensive evaluation of factors such as accuracy in relation to computational costs and energy consumption, compared to traditional machine learning or statistical methods. This analysis requires a keen analytical approach and a deep understanding of both contemporary and classical methodologies in energy system analysis, contributing to the advancement of future energy infrastructure management. You will research state of the art in foundational models and their application to energy systems You will develop and apply new models to existing tools Moreover, you will support the implementation of extensive benchmarking of models with realistic energy time series You will contribute to a publicly funded research project You take part in exciting research: From conceptualisation and software development to initial field tests In addition, you will ensure the protection of the work results through patent applications Use your skills to move the world forward. You completed very successfully your university studies in the fields of power engineering, electrical engineering, informatics or data science with focus on energy systems, optimization and time series analysis You already gained first experience or have strong interest in modeling and simulation of energy systems First experience or strong interest in time series forecasting First experience or strong interest in foundational models You have strong interest in the energy sector and the transformation of the energy system You are proficient in software development tools (e.g. Visual Studio Code) as well as frameworks for modelling time series (e.g. darts, sktime) and programming languages (Python) You are fluent in English and German We’ve got quite a lot to offer. How about you? www.siemens.de if you wish to find out more about Siemens before applying. 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. sagthesis