The Methodology Group at ALBA develops the scientific methodologies, algorithms and software needed to process and analyse large and heterogeneous datasets, supporting academic and industrial users in tackling complex scientific problems. This postdoctoral position is dedicated to the scientific data analysis activities of the IMAGiC project, with a strong focus on extracting materials-science insight from multimodal X-ray and electron datasets.
The position is framed within the project (IMAGiC), ref. CPP2024-011400, funded by MICIU/AEI. The project investigates additive manufacturing of metals for GigaCasting applications; ALBA leads the in-situ high-energy X-ray diffraction analysis and the development of data analysis tools for the resulting datasets, in collaboration with the other entities in the project consortium (ROVALMA, CENIM-CSIC and EURECAT).
The selected person will report to the Head of the Methodology Group and will work in close synergy with beamline scientists, the Joint Electron Microscopy Center at ALBA (JEMCA), the Computing Division, the Industrial Office,



with the project partners and with external partners as required. The role emphasis is on the development and implementation of a data analysis workflow optimal for the physical and materials-science interpretation of the data, supported by modern data-analysis, AI/ML and software methods.
Specifically, the responsibilities will include:
- Analysing and interpreting multimodal experimental data from the IMAGiC campaigns, combining in-situ high-energy X-ray diffraction with complementary X-ray absorption spectroscopy, computed tomography and 4D-STEM, to characterise phases, microstructure, chemical composition and their evolution under processing conditions.
- Developing and applying data-analysis methods and scientific software (in Python or equivalent) for the reduction, processing and quantitative analysis of these datasets, including data-driven and machine-learning approaches (e.g. decompo

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