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MSc or BSc Thesis / Internship (m/f/d) AI for Intent-Based Networking

ABB
Germany  Mannheim, Germany
Internship, IT/Technology, English
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Job Description:

At ABB, we help industries run leaner and cleaner-and every person here makes that happen. You'll be empowered to lead, supported to grow, and proud of the impact we create together. Join us and help run what runs the world.

This position reports to:R&D Team Lead - Secure Connected Systems

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You want to support industrial research projects and teams with your interest in network management and orchestration technologies, developing methods to automate network operation beyond office IT for industrial use-cases with state of the art networking technologies? Then join ABB, a global key player in industrial automation and smart electrification, as an intern or student worker. Apply your skills and grow personally in a challenging and fascinating environment.

ABB is a technology leader driving the digital transformation of industries toward autonomous industrial plants and buildings. Industrial systems comprise automation systems, networks and devices, software tools and platforms, and control solutions.

In the ABB Research Center Germany, we focus on innovating digital industries and smart and sustainable electrification systems. In our team, we contribute to these goals with connectivity, system integration, and applied security competencies. Become a member of our team and be part of the projects and research teams and their endeavor of demonstrating great results in an industrial automation environment and by supporting with UX approaches as well as prototype user interfaces.
Key responsibilities

The work model for the role is: #LI-Hybrid

You will be mainly accountable for:

* In close collaboration with our research team, you will be developing a concept to automatically generate requirements for automation networks from textual specifications.

* Analyzing the problem and conceptualizing a solution concept: define a target information model to capture the requirements. Consider the different types of traffic and specifications, which might require different approaches to extract the needed information.

* Implementing the concept: build the conversion concept using existing frameworks. Create a user interface to show, modify, add and audit the extracted requirements.

* Verification: use real project data to test the implementation. Define and run an approach to assess the quality and coverage of the result, i.e. the validity of the requirements and potential gaps in the extraction process.
Qualifications for the role
* We expect you to bring creativity, initiative, and result orientation to support driving our innovations toward new products and services.

* You have a study background in computer science or a related engineering discipline. You bring experience with machine-learning technologies, preferably for both software development and knowledge extraction. A further knowledge of ontologies and knowledge-graphs or industrial communication is a benefit.

* You are highly motivated, team-minded, and able to work independently.

* Fluent English in verbal and written form is required.

Interested in joining our team? We are looking forward to receiving your complete application (CV, Cover letter, Transcript of records) through our online tool. In the case of equal suitability, people with severe disabilities and their equals are given preference.

ABB AG
+49 (0) 621 381 3500

Be part of something bigger. This is where progress is powered, teams initiate action, and we move the world forward-together.
Run What Runs the World.

#ABBCareers
#RunwithABB
#Runwhatrunstheworld

Building a cleaner, smarter future takes all kinds of minds: the curious, the courageous, and the creative. That's why we welcome people from all backgrounds and experiences.

Ready to make an impact?

Apply today or visit https://www.abb.com to learn more about the impact of our solutions across the globe

Source: Company website
Posted on: 08 Aug 2026 (verified 09 Aug 2026)
Type of offer: Internship
Industry: Energy / Utilities
Languages: English
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