Home / Jobs / Master Thesis - Using LLMs for FMEA-Based Anomaly Detection and Root Cause Analysis for FCEV
Posted:
June 04, 2026
Location:
Göteborg, Västra Götaland County, Sweden

Job Description

Transport is at the core of modern society. Imagine using your expertise to shape sustainable transport and infrastructure solutions for the future. If you seek to make a difference on a global scale, working with next-gen technologies and the sharpest collaborative teams, then we could be a perfect match. 

What you will do

In this thesis project, you will use Large Language Models (LLMs) and machine learning to build a workflow that spans from structured reliability analysis to detection and diagnosis.

You will have the opportunity to:

  • Use truck specifications and system descriptions to generate and structure FMEAs for selected fuel cell truck components and functions
  • Define how the FMEA can be operationalized into signals, metrics, and hypotheses that are testable in logged vehicle data
  • Design and prototype machine learning based anomaly detection methods to identify early signs of issues before they manifest as vehicle...

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    Job Overview

    Job Type: Student
    Location: Göteborg, Sweden
    Posted: June 04, 2026
    Deadline: July 14, 2026