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Master Thesis: Grain Size Analysis from SEM/LOM Images – Utilizing EBSD Data for Enhanced Accuracy
2 months ago
Swerim AB, a leading research institute, is seeking a highly motivated master student to contribute to a cutting-edge project focused on grain size analysis from SEM/LOM images. The project aims to develop robust methods for grain size analysis, potentially incorporating EBSD images and results in the training process.
Project OverviewThe project will be supported by the META research consortium at Swerim, along with Swerim's internal resources. META is a consortium focused on research in metallography and microanalysis, emphasizing method development, demonstrating new techniques, and offering courses and seminars. META includes 13 member companies.
Key Objectives- Develop robust methods for grain size analysis from SEM/LOM images
- Explore the potential of machine learning and deep learning methods for identifying grain boundaries from images
- Integrate EBSD images and results in the training process for enhanced accuracy
The ideal candidate should have a master's degree in materials science, mathematics, or physics, with experience in Python programming and strong communication and presentation skills. Additionally, the candidate should be patient in understanding microstructures of metallic materials and interested in exploring how microstructure impacts material properties.
What We OfferSwerim AB offers a unique opportunity to contribute to a groundbreaking project, working closely with a team of experts in the field. The project is intended for a master thesis (30hp) and will be performed at Swerim in Kista, Stockholm. Swerim rewards the student with a competitive stipend for an approved master thesis (30hp).
