In cooperation with the Chair of Optical Systems Technology (TOS), the Fraunhofer Institute for Laser Technology ILT—Europe’s leading center for contract research and development in the field of laser technology—is offering the opportunity to write a thesis on the topic: »AI-based local quality prediction for laser powder bed fusion«.

We are currently developing machine learning-based approaches to make the laser powder bed fusion (LPBF) process more efficient and improve its quality. To this end, a scalable database of sensor and process data is being created, which serves as the basis for ML models for component segmentation, strategic path planning and process optimisation. The aim is to enable data-driven solutions for the automated analysis of melt pools, porosity and other quality-relevant parameters in 3D printing.

Be part of change

You will develop a modular data structure for storing sensor and metadata
In doing so, you will create a simple surrogate model for mapping quality-related parameters
For validation purposes, you will conduct initial test series and analyse the results
Finally, you will check whether the model can reliably predict the parameters of a demonstrator component

What you contribute

You are studying industrial engineering, physics, computer science, mechanical engineering, computational engineering science or a comparable engineering degree programme
You are already familiar with programming in Python and have gained initial insights into data science and signal processing
Your working style is characterised by independence, structure and good organisation

What we offer

Team spirit: Creative, interdisciplinary environment with a motivated team, flat hierarchies, and a casual culture .
Workplace: Excellent equipment with machines and devices as well as top-notch office facilities.
Co-design: Practice-oriented thesis in an innovative environment of applied research.
Work-life balance: Benefit from flexible working hours based on trust.
Accessibility: Good transport connections, parking spaces directly in front of the institute, an E-charging station, and a parking garage.

The position is limited in duration until completion of the thesis.

We value and promote the diversity of our employees' skills and therefore welcome all applications – regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. Our tasks are diverse and adaptable – for applicants with disabilities, we work together to find solutions that best promote their abilities.

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.

Ready for a change? Then apply now and make a difference! Once we have received your online application, you will receive an automatic confirmation of receipt. We will then get back to you as soon as possible and let you know what happens next.

Questions about this position will be answered by:

Julius Neuß M.Sc.
+49 241 8906-8049

Fraunhofer Institute for Laser Technology ILT

Requisition Number: 85472Application Deadline: 10/31/2026

Thesis: AI-based local quality prediction for laser powder bed fusion

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