Internship: AI/ML Applications for Materials Science and Electron Microscopy

Work Schedule
Standard (Mon-Fri)
Environmental Conditions
Office
Job Description
At Thermo Fisher Scientific, our mission is to enable our customers to make the world healthier, cleaner, and safer. We help solve complex scientific challenges, drive technological innovation, and support research that makes a positive impact on society. Our values (Integrity, Intensity, Innovation, and Involvement) guide how we work together.
As an AI/ML Applications Intern, you will join our AI Applications team within R&D in Eindhoven. You will explore how artificial intelligence and machine learning can improve electron microscopy workflows for materials science, with a focus on intelligent acquisition, microscope navigation, image analysis, and workflow optimization.
Our R&D environment provides direct access to state-of-the-art electron microscopes and extensive experimental datasets. This allows you to work on real scientific problems, develop and evaluate your ideas using experimental data, and contribute to practical improvements in microscopy.
Your project will be defined together with the team and adapted to your background, interests, and learning objectives. Possible research directions include:
Microscope stage navigation: Develop ML-based approaches to compensate for stage positioning errors and improve navigation accuracy.
Tilt and alignment: Explore AI-assisted methods for sample tilt and alignment using information from multiple images.
Spectral prediction and denoising: Investigate neural networks that use high-angle annular dark-field (HAADF) images to predict or denoise energy-dispersive X-ray spectroscopy (EDX) spectra and elemental maps.
Segmentation and image analysis: Develop automated analysis workflows that support smarter microscopy experiments and acquisition decisions.
These topics bring together machine learning, computer science, and physics. Electron microscopy supports research in sustainable battery materials, next-generation semiconductor technologies, and life sciences, including the development of new medicines.
Job Responsibilities:
Define a focused research question and project plan together with your supervisors.
Review relevant scientific literature and identify promising AI/ML approaches.
Prepare and analyze experimental microscopy datasets.
Develop, implement, and evaluate algorithms for the selected research direction.
Work with microscopy and software colleagues to assess performance and practical applicability.
Document your methods and results, and present your findings and recommendations to the team.
Job Requirements
Currently pursuing a degree in Physics, Mathematics, Informatics/Computer Science, Electrical Engineering, or a related field.
Strong interest in physics, materials science, and AI/ML.
Hands-on programming experience, preferably in Python.
Basic understanding of machine learning and numerical or data-analysis methods.
An analytical mindset and willingness to investigate open-ended scientific problems.
Good written and spoken English communication skills.
Desire to work in a collaborative, interdisciplinary R&D environment.
Availability for regular on-site work in Eindhoven and the ability to travel there throughout the internship.
Experience with deep learning frameworks, image processing, electron microscopy, or spectroscopy is welcome. The project scope can be adapted to your existing knowledge and skills.
Internship Details
Location: Eindhoven, the Netherlands.
Start date: From 1 October 2026.
Duration: Until approximately April 2027.
Compensation: Internship compensation is provided.
On-site presence: Regular attendance in Eindhoven is required.
Why join our team
At Thermo Fisher Scientific, we offer an inclusive and collaborative environment where you can learn from experienced researchers and developers. You will gain hands-on experience at the intersection of AI and experimental science, with access to advanced microscopy equipment and real research data.
Through a project tailored to your interests and background, you will strengthen your research and technical skills while contributing to tools that help scientists understand materials and improve their experiments. Join us and help accelerate research and scientific innovation.
Apply now!