Thesis (Master): Evaluation of Standardized Physical Device Interaction by AI Agents

Siemens; Bayern; On-site; EUR 12,000 - 18,000; Full time

Job summary

Siemens in Erlangen invites a Master’s thesis student to explore AI-driven hardware interaction. You will join a team working on autonomous discovery, control, and safe operation of industrial devices using standardized descriptions and modern AI agents.

The role blends software and hardware interfaces with real-world industrial protocols. Ideal candidates are pursuing a Master’s in CS/EE/Robotics, proficient in Python, familiar with C/C++/Rust, and have exposure to LLM integration and

Qualifications

• Currently enrolled in a Master’s program in Computer Science, Electrical Engineering, Robotics, or a related field.
• Strong proficiency in Python; knowledge of C/C++ and Rust is beneficial.
• Experience with LLM integration and agentic AI software development.

Responsibilities

• Work on enabling autonomous discovery and control of physical devices via standard interfaces.
• Evaluate performance of LLMs in semantic discovery tasks for device interaction.
• Analyze description standards (MCP, MHS, OPC UA, WoT, AsyncAPI) for token efficiency, interface quality and safety.
• Research methods to deterministically extract hardware safety limits from device metadata.

Skills

Python

C/C++

Rust

LLM integration

OPC UA

Web of Things

Education

Master's degree in Computer Science/Electrical Engineering/Robotics

Tools

OPC UA

Web of Things

Job description

Location: Erlangen
Department: FT RPD CPC SSI-DE
Mode of Employment: Fixed Term / Full-Time; (35 hours / week)

Overview

Future autonomous systems, such as mobile robots, must be capable of dynamically adapting to their environment by utilizing available hardware as tools. Instead of relying on pre-programmed drivers, these systems should autonomously discover and interface with devices on-the-fly. This thesis explores how Large Language Models (LLMs) can bridge the gap between high-level intent and physical hardware interaction through standardized device descriptions. What´s the goalReady to bring the future of AI-driven hardware interaction to life? Join us in Erlangen as a Master's Thesis student and help pioneer how intelligent agents autonomously discover, control, and safeguard physical devices in real-world environments!

What we offer you

• Exciting research and development projects that put your theoretical knowledge into practice
• Individual supervision and support from experienced experts in your field
• Access to the latest technologies, laboratories, and resources
• Diverse opportunities to contribute your ideas and actively shape the projects
• Excellent career opportunities through contact with potential employers

You'll make an impact by

• You currently study successfully in a field such as Computer Science, Electrical Engineering, or a related discipline, applying your academic knowledge to real-world device interaction challenges
• Building on this foundation, you evaluate the performance of large language models (LLMs) in semantic discovery tasks, probing and mapping unknown physical devices via various industrial communication protocols
• Subsequently, you analyze and compare description standards—such as MCP, MHS, OPC UA, W3C WoT, and AsyncAPI to assess their impact on token consumption, expressiveness, interface quality, safety, and reliability
• In addition, you research and implement methods to deterministically extract hardware safety limits from device metadata, ensuring the absence of physical damage during autonomous operation
• Finally, you investigate approaches for autonomous authentication and access control, contributing to the secure configuration of devices in dynamic, ad-hoc environments

Education

You are currently enrolled in a Master's program in Computer Science, Electrical Engineering, Robotics, or a related field.

Experience and Skills

• Strong proficiency in Python; knowledge of C/C++ and Rust is beneficial
• Experience with LLM integration and agentic AI software development
• Basic understanding of hardware-software interfaces and measurement technology, with an interest in industrial communication protocols such as OPC UA and Web of Things

Ways of Working

You work independently and thrive on exploring complex, innovative system architectures.

Languages

• Very good English skills are required

About Us

At Siemens, we believe that feeling valued and included is the foundation for doing great work. That’s why we aim to create an inclusive workplace where everyone feels a sense of belonging, and where individual perspectives and experiences are celebrated. Our commitment to fairness and respect extends to every applicant. As an equal opportunity employer, we welcome applications from individuals of all backgrounds and particularly encourage applications from persons with disabilities. In the case of equal qualifications, severely disabled applicants and applicants with equivalent status will be given preference.

The world never stands still. And new challenges arise every day. With a passion for questioning things, for supplying ideas, and intelligently driving things forward we are helping society move towards a smarter tomorrow. Be it with technologies that reduce carbon emissions in cities or hyperintelligent robots. This is how we are able, to tackle the most important projects and push them forward together. Help us shape the future.

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