🚀 Research Scientist: Machine Learning Engineer – AI-Powered Image Analysis

Offer Description

About us

The DWI – Leibniz-Institute for Interactive Materials is a federal and state funded research institute of the Leibniz Association based on the Melaten Campus of RWTH Aachen University in Germany. International young and experienced scientists from various disciplines develop interactive materials based on the principles of nature. It is a location at which people with different talents, experiences and skills work together, in order to learn from one another and generate new knowledge and new methods to create a better quality of life in our world.

DWI offers you a wide range of possibilities to develop further both professionally and personally in an interdisciplinary setting.

Position

DWI is looking to fill the position as soon as possible:

Research Scientist
Machine Learning Engineer -AI-Powered Image Analysis

The Project

HairSense is a translational project at the DWI – Leibniz Institute for Interactive Materials in Aachen with the clear goal of creating a spin-off. We are developing a platform technology for the automated analysis of keratin fibers – ranging from luxury fibers such as cashmere to human hair. At the core of the project is the combination of state-of-the-art imaging with AI-powered image analysis to establish objective, fast, and scalable testing methods for the textile and cosmetics industries.

• Development and implementation of AI/ML models (Deep Learning, Computer Vision) for image data analysis.
• Data preparation, annotation, and training of models for structural recognition in biological and textile samples.
• Building automated pipelines for image analysis, classification, and report generation.
• Participation in sample preparation and image acquisition in order to understand the data generation process and optimally integrate it into model development.
• Close collaboration with an interdisciplinary team from materials science, computer science, biology, and business development.
• Contribution to publications, fundraising for research grants, and presentations at national and international conferences.
• Optionally, involvement in business development (e.g., market analysis, customer benefits, and transfer towards a planned spin-off).

Your profile

• Completed degree in Computer Science, Data Science, Physics, Mathematics, Computational Biology, or related fields.
• Solid experience with Machine Learning / Deep Learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
• Strong programming skills (Python; ideally with experience in databases and cloud environments).
• Experience in image analysis and computer vision, ideally in the context of biological samples or materials science.
• Willingness to also engage in sample preparation and image acquisition.
• Ability to work in a structured, independent manner as well as enthusiasm for interdisciplinary teamwork.
• Good command of English.

DWI offers

• Exciting and challenging tasks with access to internal and external networks, training opportunities, and conferences
• Individual development plans and support from experienced specialists
• Open, team-oriented work atmosphere in an international environment
• 30 days of annual leave
• Flexible, family-friendly working conditions
• Good transportation connection with parking facilities
• Restaurants and cafeterias in close proximity

We will support the applicant to gain further qualifications. We offer our employees a broad spectrum of career opportunities in an attractive working professional environment ( At DWI we support equal opportunities; an overview on the measures can be found here:

We welcome all applications - regardless of gender, disability, nationality or ethnic and social background.

How to apply

The position is to be filled as soon as possible.

Please upload your complete application documents (curriculum vitae, copies of final and work references, letter of motivation) under "Apply for this job". Till Hülsmann will answer any questions you may have about the position ( ).

By submitting an application, you consent to your data being processed electronically.