TEM Scientist – Automation & Data Workflows

About the role

Eurofins EAG Laboratories is seeking a hands-on Transmission Electron Microscopy (TEM) Scientist who also has strong experience building automation, scripting, or data workflows for microscopy data. This is a specialized, hybrid role combining advanced TEM operation and applied automation/data science in a production laboratory environment.

Responsibilities

• Design, build, and implement automation workflows directly on S/TEM systems (data acquisition, instrument control, and workflow scripting)
• Develop and maintain automated pipelines for TEM data collection and analysis
• Perform image processing (segmentation, enhancement, measurement, visualization) on 2D and 3D datasets
• Apply computer vision, statistics, and machine learning to microscopy and analytical data
• Work with multi-modal materials characterization data (TEM, SEM, EDS, XRD, XPS, RBS, etc.)
• Improve throughput, repeatability, and data quality of TEM-based services
• Build tools for data processing, feature extraction, and exploratory analysis
• Partner with lab teams to translate real-world analytical problems into automated solutions
• Support S/TEM operation and data collection, including EDS/EELS where needed
• Contribute to new TEM capabilities (e.g., 4D STEM, advanced imaging workflows)

Qualifications

• MS or PhD in Materials Science, Physics, Engineering, or related field
• Hands-on S/TEM experience, including real-world data collection
• Experience developing or implementing automation for TEM or similar instrumentation (e.g., scripting acquisition, using vendor APIs, workflow automation)
• Strong Python programming skills
• Experience applying data science, statistics, or computer vision to experimental data
• Experience working with materials-focused systems (e.g., semiconductors, metals, ceramics, failure analysis)
• Experience with EDS (not just exposure to EELS)
• Ability to work in a fast-paced, production lab environment

Preferred Qualifications

• Experience with machine learning applied to imaging or scientific datasets
• Familiarity with deep learning frameworks (PyTorch, TensorFlow)
• Experience with TEM automation frameworks or vendor APIs
• Experience with large-scale or high-throughput data pipelines
• Exposure to 4D STEM or advanced TEM techniques
• Experience working with multi-modal data (image, spectral, time-series)