Into work, get set, go!
Our interns have ideas, make things happen, and get involved – from the very first day. Be part of a team numbering more than 290,000 talented people who are dedicated to tacking the most important challenges. What will the world look like in 20 years in terms of electrification, automation, and digitalization? Let’s find out together! You might want to turn established thinking on its head in the search for solutions. When you join our team, we give you the freedom to do so. You will also have all the benefits of a company with an excellent international network. What are you waiting for? Shape your future with us.
We make real what matters. This is your role.
- During your internship you will work on the topics of preprocessing, feature engineering and prediction of energy time series such as electrical loads, feed-in by renewable energies as well as electromobility
- You will gain insights into data modeling, data analysis, statistical methods and machine learning methods
- Furthermore, you implement and benchmark algorithms and methods for the prediction of time series
We don’t need superheroes, just super minds.
- You are currently enrolled in a master’s degree for electrical engineering, energy management, computer science, data science, industrial engineering or a comparable course of study
- You are interested in the energy sector and the energy transition
- Ideally, you have knowledge in statistics, data analysis and modeling - experience with Python (e.g., numpy, pandas, sklearn, darts, sktime) is required
- You are curious, work independently and determinedly and possess initiative as well as a willingness to learn
Duration of the internship is based on university regulations.
Make your mark in our exciting world at Siemens.
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If you have more questions please contact: www.siemens.de/fragenzurbewerbung
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.
Company: Siemens AG
Experience Level: Student (Not Yet Graduated)
Full / Part time: Full-time