Master’s Thesis - LLM-Based Narrative Virality Analysis and Signal Design in Economic and Market Text

役割について

勤務地
ドイツ
Bayern
Erlangen
  • 国: ドイツ
  • 市: Muelheim an der Ruhr

  • 国: ドイツ
  • 州/県/国: Hamburg
  • 市: Hamburg

在宅勤務 又は 事務所勤務
ハイブリッド勤務（在宅勤務/事務所勤務）
会社
Siemens Energy Global GmbH & Co. KG
組織
SE CFO
部署
Gas Services
フルタイム/パートタイム
フルタイム
経験レベル
学生
Location: ERL S SK 3

Mode of Employment: Full-time / Fixed Term


A Snapshot of Your Day 

You work with public economic and market-related text and investigate how narratives spread across sources and time. Your focus is on exploring LLM-based methods for measuring narrative spread, salience, and persistence, and on transforming these dynamics into structured and interpretable signals.

How You’ll Make an Impact 
  • Development of a research framework for measuring narrative spread and salience in public economic and market-related text
  • Exploration of LLM-based and clustering-based methods for identifying coherent narrative themes across sources and time
  • Implementation of a prototype for virality-oriented or spread-based signal generation from textual data
  • Evaluation of different dimensions of narrative spread, such as speed, source diversity, persistence, and cross-source propagation
  • Documentation of methodology, findings, and limitations for future reuse in applied text and data analytics
  • Support with the translation of research outcomes into interpretable signal concepts for forecasting-related use cases
What You Bring
  • Studies in Data Science, Computer Science, Artificial Intelligence, or a related field at Master’s level
  • Knowledge of Python-based data processing , NLP, or text-mining workflows for text analysis and prototyping
  • Interest in large language models, prompt-based methods, narrative analysis, and information diffusion in economic,  business, or market-related settings
  • Understanding of clustering, similarity analysis, or time-based signal construction for text-driven indicators
  • Ability to work independently on implementation, analysis, and technical documentation in an applied research environment
  • Experience with embeddings, public text datasets, event analysis, or experimental evaluation as an advantage 
About the Team

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. 

Rewards/Benefits 
  • Exciting insights into an international company  
  • Lay the foundation for your career with us  
We value equal opportunities and welcome applications from people with disabilities.

#RPO