Software Engineering / AI Engineering Intern
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工作时间 标准（周一至周五） 工作环境 办公室 职位描述 毕业设计：数据辅助诊断和预测性维护 级别：HBO学士学位或WO学士/硕士毕业项目 相关专业：软件工程 地点：赛默飞世尔科技，埃因霍温研发中心，透射电子显微镜(TEM) 介绍 赛默飞世尔科技开发有助于客户让世界变得更健康、更清洁、更安全的技术和服务。埃因霍温是其透射电子显微……
职位描述 · 原文
Work Schedule
Standard (Mon-Fri)
Environmental Conditions
Office
Job Description
Graduation assignment: Data-assisted diagnosis and predictive maintenance
Level: HBO bachelor or WO bachelor/master graduation project
Relevant studies: Software Engineering
Location: Thermo Fisher Scientific, Eindhoven R&D, Transmission Electron Microscopy (TEM)
Introduction
Thermo Fisher Scientific develops technologies and services that help customers make the world healthier, cleaner, and safer. Eindhoven is its primary technology location for Transmission Electron Microscopy (TEM), bringing together R&D, manufacturing, and service expertise. Thermo Fisher Scientific in Eindhoven
TEM instruments use electrons to reveal structures at extremely small scales, supporting research in life sciences and materials science. This assignment explores how software can help engineers diagnose problems in these complex instruments more efficiently.
Background and objective
Service engineers use system logs, bug reports, calibration files, and technical procedures to investigate failures. This information is often spread across multiple sources, making diagnosis time-consuming and dependent on individual experience.
The objective is to develop and evaluate a software prototype that combines historical system data with service knowledge to suggest likely causes and useful diagnostic checks.
Research question
How can historical system data and service knowledge support faster and more reliable diagnosis of a selected TEM system problem?
The student will investigate which data sources are useful, compare suitable technical approaches, and measure the prototype’s value against the current diagnostic process.
Scope and approach
The project focuses on one failure mode or a closely related group of problems, such as an offline module or recurring performance issue.
The student will:
Analyse the current diagnostic process with service engineers.
Assess and prepare relevant data and technical documentation.
Compare approaches such as structured search, diagnostic rules, and an LLM-based assistant.
Build a prototype that provides diagnostic suggestions with supporting evidence.
Evaluate diagnostic accuracy, diagnosis time, and usability using historical cases and engineer feedback.
The prototype is intended for internal evaluation. Predictive maintenance may be explored as an extension if sufficient degradation or failure data is available.
Deliverables
A research plan and assessment of available data.
A working prototype with documented code and usage instructions.
An evaluation against the current diagnostic approach.
A graduation thesis, final presentation, and recommendations for further development.
Intern requirements
We are looking for a student who:
Is enrolled in an HBO or WO Software Engineering programme and is ready to start a graduation assignment.
Has programming experience, preferably in C#. Python is also acceptable.
Understands software design, testing, and version control.
Can analyse data and approach technical problems systematically.
Can work independently and collaborate with software engineers and service specialists.
Communicates clearly in English, both verbally and in writing.
An interest in AI, machine learning, or information retrieval is welcome. Prior knowledge of electron microscopy is not required.
Apply today!
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