Siemens Energy

Master thesis: Deprecated word replacement in technical documents.

A Snapshot of Your Day

As a graduate student working on your master's thesis at Siemens Energy, you will concentrate on improving a machine learning model that standardizes technical terms in different documents. Your daily tasks may involve:

• Studying previous work done on terminology standardization to understand the current landscape and identify potential areas for improvement.

• Gathering and analyzing existing technical documents to extract remarkable nouns, which will form the basis of a comprehensive word list.

• Applying this word list to determine preferred terms and identify those that should be phased out for consistency.

• Preprocessing data to prepare it for input into the machine learning model.

• Programming and refining the algorithm to improve its ability to recognize and accurately adjust terminology inconsistencies.

• Conducting tests to guarantee the model's precision and efficiency, detailing your progress, and making improvements based on outcomes.

• Regularly consulting with a team of experts to gain feedback and integrate their knowledge into your project for a well-rounded approach.

By taking a comprehensive and strategic approach to your day, you can build on previous research and contribute to a more efficient terminology standardization system.

How You’ll Make an Impact

Your work on this master thesis will have a significant impact on Siemens Energy by ensuring the precision and clarity of technical documentation. By refining the machine learning model to accurately standardize terminology, you will:

• Improve communication across different departments and collaborators, reducing misunderstandings and errors in translations.

• Boost the quality and consistency of customer documentation, encouraging a more professional and reliable image of Siemens Energy.

• Optimize the process of integrating data from various sources, thus reducing mismatch risks and saving time and resources.

• Contribute to the creation of a structured and standardized database for technical terms, which will serve as a reference point for future projects and documentation.

What You Bring

To be successful in your application for this master thesis opportunity at Siemens Energy, you should have the following qualifications and skills:

• Currently pursuing a master's degree or equivalent experience in Machine learning, Statistics, Computer Science, Data Science, or a related field.

• Strong foundation in machine learning algorithms and their application to Large Language Models (LLM) and natural language processing (NLP) tasks.

• Proficiency in programming languages commonly used in data science, such as Python.

• Experience with data preprocessing, model training, and validation techniques.

• Ability to analyze and interpret complex datasets, identifying patterns and inconsistencies.

• Previous work or academic experience related to standardization of terminology or technical documentation is a plus.

• Excellent problem-solving skills and attention to detail.

• Strong written and verbal communication skills, with the ability to articulate your work and present findings effectively.

• An open approach, enthusiastic about working in a diverse team and incorporating feedback from different collaborators.

This master thesis offers an opportunity to contribute to Siemens Energy's technical documentation processes and gain hands-on experience in applying machine learning to real-world problems.

About the Team 

You will get an opportunity to work with Application Platforms Business (APB) team, which is one of the teams in IT that is driving the End-to-end responsibility for all central applications and platforms

• Solution Architecture
• Service Management and Application Maintenance
• Operational Provider Management
• Digital Consulting 

Implementing all projects concerning central platforms. Orchestrating the governance structure of Business Partner Boards. You will get to know a global company in the forefront of new energy technology. During your time at Siemens Energy, you will also get the opportunity to establish a network for future cooperation.

Who is Siemens Energy?

At Siemens Energy, we are more than just an energy technology company. We meet the growing energy demand across 90+ countries while ensuring our climate is protected. With more than 99,000 dedicated employees, we not only generate electricity for over 16% of the global community, but we’re also using our technology to help protect people and the environment.

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 https://jobs.siemens-energy.com/en_US/jobs , id nr 266222 no later than 2024-11-29.

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

For questions about the role, please contact Shwetha Chandramouly on shwetha.chandramouly@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: 
Anders Häll, Unionen, +46122-887514 
Simon Von Eckardstein, Sveriges Ingenjörer, +46122-842 24 
Jan Lundgren, Ledarna, +46122-812 33 
Mikael Malmgren, IF Metall, +4676-6958685

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