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Mandatory internship (f/m/d) Data Science in the context of forecasting of energy timeseries
Vue: 164
Jour de mise à jour: 18-10-2024
Localisation: Erlangen Bavaria
Catégorie: Éducation / Formation
Industrie: Appliances Electrical Electronics Manufacturing
Niveau: Entry level
Type d’emploi: Full-time
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le contenu du travail
Mode of Employment: Limited; Full time onlyInto 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
- 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
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Date limite: 02-12-2024
Cliquez pour postuler pour un candidat gratuit
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