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: Archeometallurgical analyses SEM-EDS microscopy and chemical composition analysis of iron artifacts, slags, and ores GIS spatial analysis, statistical analysis, and network analysis of iron production Other
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operating and interpreting data from analytical and characterization equipment, including: Universal Mechanical Testing Machine Scanning Electron Microscope (SEM) DTG thermal analyzer FT‑IR spectroscopy
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techniques (SEM/EDS, chemical analyses) is an asset. · Skills in digital tools and scientific programming (Python, MATLAB, or equivalent) are desirable; experience with AI methods is a plus but not mandatory
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on Ni-based superalloys and/or Ti-alloys (SEM, EDS, EBSD, TEM, etc.) Personal competences in accordance with the requirements profile including specification (e.g. social skills, meaning that you enjoy
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expertise in chemical and petrological analysis techniques such as XRF, SEM, or EMPA. Experience in petrological modelling using tools such as THERMOCALC, Perple_X, Theriak-Domino, or MageMin is important
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machine learning. A special emphasis will be placed on the correlative combination of the experimental capabilities of scanning electron microscopy (SEM), electron probe micro analysis (EPMA), transmission
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relevant research experience. You should have strong practical experience in fieldwork, mapping, and sample collection, alongside expertise in chemical and petrological analysis techniques such as XRF, SEM
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inorganic nanomaterials (XRD, UV-Vis, XPS, TEM/SEM, BET, TGA, FTIR, Raman) • Practical skills: inorganic synthesis and/or catalytic evaluation • Basic knowledge of quantum physics, fluid mechanics and
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characterization tools such as VSM, SQUID magnetometer, SEM, XRD, XRF, TGA, DSC, etc. Department Unit/Website: www.ameslab.gov Proposed Start Date: June 1, 2026 Proposed End Date or Length of Term: May 31, 2027
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., SEM, XRD, FTIR, mechanical testing). Proficiency in data analysis tools (Python, MATLAB, JMP) and technical documentation. Strong analytical skills and attention to detail. Excellent written and verbal