Scientist, TEM Analysis

Eurofins•Phoenix, AZ

3h•$115,000 - $130,000•Onsite

About The Position

Eurofins EAG Laboratories has over 40 years of experience in engineering and materials testing services, operating as part of Eurofins Scientific, a multi-billion-dollar global leader. At EAG, curiosity drives their work in understanding materials and product capabilities, supporting diverse industries from semiconductors and advanced electronics to pharmaceuticals, medical devices, energy systems, and consumer products. They utilize advanced techniques in analytical chemistry, microscopy, surface analysis, and engineering sciences to help clients solve complex challenges across the product lifecycle. The company prides itself on its world-class instrumentation and its people, who are problem solvers, collaborators, and lifelong learners valuing precision, curiosity, and impact. Eurofins EAG Laboratories is seeking a Scientist, TEM/Data Science to support and advance data-driven analysis across their materials characterization and analytical testing services, with a strong emphasis on Transmission Electron Microscopy (TEM). This role involves applying data science, statistics, and machine learning to complex, multi-modal laboratory data generated from a broad range of analytical techniques. The Scientist will partner closely with engineers, scientists, and operational teams to improve data quality, automation, insight generation, and analytical capabilities in support of client-driven testing services.

Requirements

MS or PhD in Materials Science, Data Science, Engineering, Physics, Chemistry, or a related field.
Strong background in TEM principles, operation of S/TEM, EDS/EELS, and automation.
Demonstrated experience applying data science or statistical methods in a laboratory, engineering, or applied science environment.
Proficiency in Python and common scientific data analysis libraries (e.g., NumPy, Pandas, SciPy, scikit-learn).
Experience working with experimental, sensor, image, spectral, or time-series data.
Strong written and verbal communication skills.
Strong foundation in statistics, data analysis, and applied machine learning.
Ability to evaluate model performance and understand limitations of scientific datasets.
Familiarity with machine learning frameworks such as PyTorch or TensorFlow for applied use cases.
Experience with data visualization and scientific reporting.
Ability to work collaboratively in a fast-paced, client-focused analytical services environment.
All considered applicants must be U.S. Persons as defined by ITAR: U.S. Citizen, U.S. Permanent Resident (i.e. “Green Card Holder”), or Political Asylee or Refuge.

Nice To Haves

Experience applying advanced machine learning techniques such as deep learning or representation learning to scientific datasets.
Familiarity with image, spectral, time-series, or multi-modal data modeling.
Exposure to modern neural network architectures (e.g., CNNs, RNNs, transformers) and understanding when advanced methods are appropriate.
Knowledge of signal processing or feature extraction techniques used in scientific instrumentation data.
Familiarity with model lifecycle practices such as experiment tracking, versioning, and reproducibility.

Responsibilities

Support the data process from various materials characterization techniques including TEM, SEM, EDS, XRD, XPS and RBS.
Develop and tune TEM automation on cutting edge TEM microscopes.
Perform image processing - including image enhancement, segmentation, measurement and visualization on 2D and 3D data sets.
Responsible for building algorithms and developing software to automate the TEM data collection and processing using computer science techniques (computer vision, machine learning, etc.).
Apply data science and machine learning methods to analyze, model, and interpret materials characterization data across multiple analytical techniques, including microscopy, spectroscopy, diffraction, and other physical or chemical testing methods.
Proactive in developing new TEM technologies (such as 4D STEM) to meet new demands from customers.
Collect S/TEM, EDS/EELS data and prepare reports per instructions.
Support TEM jobs including S/TEM, EDS/EELS.
Develop and maintain data analysis workflows and pipelines that improve efficiency, reproducibility, and scalability of laboratory data processing.
Perform statistical analysis, feature extraction, and exploratory data analysis to identify trends, anomalies, and correlations in experimental data.
Build, validate, and document predictive or classification models to support materials characterization, failure analysis, process optimization, and customer reporting.
Collaborate with laboratory scientists and engineers to translate experimental and customer questions into data-driven solutions.
Support automation and standardization of data collection, processing, and reporting where appropriate.
Communicate analytical results clearly to technical and non-technical stakeholders.
Contribute to continuous improvement initiatives related to analytical capabilities, data infrastructure, and quality systems.