Master Thesis: Evaluating Time Series Foundational Models for Forecasting and Analytics in Industrial Applications

Über die Aufgabe

Standort
Schweden
Oestergoetlands laen
Finspang
Unternehmen
Siemens Energy AB
Organisation
EVP Global Functions
Geschäftsbereich
Digital Core
Vollzeit / Teilzeit
Vollzeit
Erfahrungsniveau
Studierende

A Snapshot of Your Day

As a master’s thesis student at Siemens Energy, you will explore the latest advancements in foundational time series forecasting models, as well as different forecasting strategies like zero shot and few shot forecasting. Your project will benchmark these models and strategies against conventional forecasting methods on real-world use cases such as equipment lifetime prediction and remote diagnostics data. You’ll investigate how these models, which require no annotated datasets, can deliver scalable, reusable, and highly accurate forecasts—helping us optimize maintenance, improve reliability, and drive digital transformation in our Gas Services division.


How You’ll Make an Impact

  • Evaluate state-of-the-art foundational time series models on company-specific datasets.
  • Benchmark model performance against traditional forecasting approaches for equipment lifetime and remote diagnostics.
  • Evaluate and compare different forecasting strategies on the data sets as well.
  • Identify opportunities for scalability and reusability across multiple forecasting tasks.
  • Deliver actionable insights to improve predictive maintenance and operational efficiency.
  • Contribute to the adoption of advanced AI solutions in industrial settings, supporting our mission of reliable, sustainable energy.


What You Bring

  • Strong background in data science, machine learning, or statistics.
  • Experience with time series analysis and forecasting techniques.
  • Familiarity with foundational models (e.g., transformers, large pre-trained models) and zero-shot learning concepts.
  • Programming skills in Python or similar languages; experience with ML libraries (TensorFlow, PyTorch, etc.).
  • Analytical mindset and ability to communicate findings clearly.


About the Team

Within our team, you will work alongside a wide spectrum of disciplines. Expect day-to-day collaboration with solution architects, ontology specialists, and data scientists with deep expertise in data architecture and advanced analytics, as well as mechanical and quality engineers who know every nut and bolt of our products. This cross-functional setting immerses you in a global company at the forefront of new-energy technology and gives you the chance to build a professional network that can drive future collaborations and career opportunities.

Our Gas Services division offers Low-emission power generation through service and decarbonization. Zero or low emission power generation and all gas turbines under one roof, steam turbines and generators. Decarbonization opportunities through service offerings, modernization, and digitalization of the fleet.


Who is Siemens Energy?

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. 

Find out how you can make a difference at Siemens Energy: https://www.siemens-energy.com/employeevideo


Our Commitment to Diversity

Lucky for us, we are not all the same. Through diversity, we generate power. We run on inclusion and our combined creative energy is fueled by over 130 nationalities. Siemens Energy celebrates character – no matter what ethnic background, gender, age, religion, identity, or disability. We energize society, all of society, and we do not discriminate based on our differences.


Application

Don’t hesitate – apply via the Apply button, id nr 286355 no later than 2025-12-14.

Ongoing selection is applied, the role might be filled before last application date.


For questions about the role, please contact hiring manager Davood Naderi on davood.naderi@siemens-energy.com

For questions about the recruitment process please contact the responsible recruiter Ermina Imamovic on ermina.imamovic.ext@siemens-energy.com


We refrain from all contact with staffing and recruitment companies, or advertising brokers.


Location: Finspång


Trade Union Representatives:
Unionen, unionen.finspang.se@siemens-energy.com
Sveriges Ingenjörer & SACO, asi.se@siemens-energy.com
Ledarna, Anders Fors, anders.fors@siemens-energy.com
IF Metall, Mikael Malmgren, mikael.malmgren@siemens-energy.com



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