Master's thesis: LLM-based interoperability for sensor networks

Master's thesis: LLM-based interoperability for sensor networks

Interoperability makes it possible for information to be exchanged between different services, because all services involved speak the same language and have the same understanding of the data that is being exchanged. However, achieving interoperability between IT services has been a longstanding problem. Sensor networks often suffer from interoperability challenges due to the large variety in the hardware and software involved. Different types of sensors may represent the same information in different ways.

Thesis project We are interested in whether and to what extent interoperability can be achieved in sensor networks through the use of generative models such as large language models. A prior study by Falcão et al. used LLMs to either perform conversions directly on the data level, as well as indirectly through the generation of code, showing promising results. They however did not consider sensor networks, which present not just a different application context but also typically produce data at a high rate, which may present unique challenges and opportunities.

Your profile We are looking for someone who has good knowledge of (applied) generative AI, hands-on experience with APIs for large language models, and documented experience with software development. An understanding of sensor networks is a plus. You are independent and inquisitive, preferably with an interest in research. You are also able to understand and assimilate research results in the form of articles, standards, and technical systems.

You are passioned about research, and open for a future PhD student position.

This is a full-time master’s thesis position, and applicants are expected to have completed all required coursework before commencing the thesis.

Your workplace The Master thesis is based on a research collaboration between LiU and RISE, and the primary workplace will be at RISE, Linköping.

RISE is Sweden's independent government research institute, with a mission to promote sustainable growth by strengthening business competitiveness public sector innovation. With applied research, more than 130 technology infrastructures for development, testing and demonstration, and interdisciplinary expertise, our more than 3,000 employees offer support and knowledge all the way – from idea to innovation and the step into the market. Through our assignments and collaborations, both nationally and internationally, we contribute to the transition towards a sustainable society.

More information and application If you are interested in the project and have questions, please contact Tomas Westlund ([email protected]) and Daniel de Leng ([email protected]). The last application date is November 1st. Selection and interviews will be conducted continuously during and after the application period. Apply without cover letter.

Sources:

R. Falcão et al., Evaluating the effectiveness of LLM-based interoperability, arXiv:2510.23893, 2025. https://arxiv.org/pdf/2510.23893