Siemens Energy

• Surveying existing dimensionality reduction and feature selection methods applicable to time series data
• Developing and testing new algorithms tailored for high-dimensional time series datasets
• Benchmarking algorithm performance against traditional approaches
• Collaborating with the research team to interpret and visualize experimental results
• Documenting methodologies and research findings for publication or internal use
• Supporting knowledge sharing and discussion within the team to advance project goals
  
  

• Enrollment as a Master’s student in Data Science, Computer Science, Mathematics, or related disciplines
• Experience with machine learning algorithms and time series analysis
• Proficiency in programming languages such as Python or R (preferably R)
• Familiarity with dimensionality reduction and feature selection techniques
• Strong analytical skills for data interpretation and algorithm evaluation
• Effective teamwork and collaboration abilities

At Siemens Energy, we are more than just an energy technology company. With ~100.000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world's electricity generation.

Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation.      

• Exciting insights into an international company
• Lay the foundation for your career with us