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Internship Process Engineering & Data Analytics for Advanced Power Systems (m/f/d)
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Data-Driven Optimization: Explore how AI and machine learning techniques can be applied to improve plant efficiency, flexibility, and availability.
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Internship Process Engineering & Data Analytics for Advanced Power Systems (m/f/d)

GE Vernova -
Baden, AG

Jetzt bewerben

Details zur Stelle

Praktikum
vor 11 Stunden

Qualifikationen

Englisch
Master
Bachelor
Python

Vollständige Stellenbeschreibung

Are you ready to embark on an engineering journey with practical experience at a global energy leader? The STEPS (Student Technology & Engineering Program Switzerland) at GE Vernova Gas Power Engineering offers a unique opportunity to gain real-world experience, learn hands-on, and collaborate with industry experts shaping the future of energy. Unlike traditional internships, this comprehensive program provides exposure to various engineering disciplines and insights into different fields. You will also have the chance to visit GE Vernova sites in Switzerland and France, witnessing innovation firsthand through facility tours and real-world applications. Enhance your professional network by connecting with GE Vernova leaders, engineers, and fellow interns, and participate in workshops, technical training, and professional development sessions designed to prepare you for future career opportunities. If you are passionate about engineering, sustainability, and innovation, this internship is your opportunity to acquire the skills and experience!

Job Description

The Role We are looking for a motivated student (nearing their Master’s degree) to bridge the gap between process engineering and data science. In this role, you will help optimize plant systems by analyzing complex operational data and developing tools to improve process efficiency. You will translate engineering challenges into digital solutions, providing you with a unique perspective on how large-scale energy systems are designed and maintained.

Our work sits at the intersection of mechanical engineering, data systems, and real-world power plant performance. You will be joining a team that directly impacts how next-generation infrastructure is designed, monitored, and optimized. In this role, you will help bridge the gap between process engineering and data science, translating complex engineering challenges into digital solutions and gaining a unique perspective on how large-scale energy systems function under real-world conditions.

What You Will Do

Data Analysis & Modeling: Process and interpret operational data to identify trends, performance bottlenecks, and optimization opportunities within power plant systems.
Process Engineering Support: Assist in the technical analysis of critical balance-of-plant systems, applying thermodynamics and fluid mechanics principles to real-world design challenges.
System Analysis: Deepen your understanding of combined cycle power plant operations, specifically the interplay between the gas turbine, heat recovery steam generator (HRSG), steam turbine cycles and balance of plant equipment.
Software & Scripting: Develop scripts and automated workflows (using languages like Python) to streamline data processing, model performance, and create visualizations. Explore opportunities to use available AI tools to support the effort.
Collaborative Design: Work alongside senior engineers to document findings and present data-driven recommendations that directly influence the design and efficiency of next-generation infrastructure.

Data-Driven Optimization: Explore how AI and machine learning techniques can be applied to improve plant efficiency, flexibility, and availability.

Who You Are

Academic Background: Currently pursuing a Master’s degree (or finishing a Bachelor’s) in Mechanical Engineering, Process Engineering, or an Energy-related field. You have a solid grasp of thermodynamics and are eager to apply this knowledge to understand the complex processes of combined cycle power plants.
Technical Proficiency: Strong programming foundation (e.g., Python) and a keen interest in applying data-driven methods to physical engineering systems. Experience with applying AI/Machine Learning methods to physical engineering or time-series data.
Analytical Mindset: You enjoy solving complex, multi-disciplinary problems and have a knack for translating raw technical data into meaningful, actionable insights.
Communication: Fluent in English, with the ability to clearly explain technical concepts to a variety of stakeholders.
Engagement: You are a proactive learner who is eager to contribute to a collaborative, international team environment.

Additional Information

Relocation Assistance Provided: No

Jetzt bewerben

Erweiterte Suche

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