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of microanalytical techniques (SEM-EDS/WDS, EMPA, Micro-XRF, LIBS, LA-ICPMS, SIMS) - Targeted geochronology studies of sedimentary, metamorphic and igneous rocks (e.g. U-Pb SIMS and LA-ICPMS analysis
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of data scientists, software engineers, and experimental researchers on topics including: Developing multi-scale and multi-modal representation learning methods for scientific imaging data (e.g., SEM
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Website https://www.academictransfer.com/en/jobs/358703/phd-in-scalable-safe-ai-for-sem… Requirements Specific Requirements A master’s degree AI, Machine Learning, Data Science, Computer Science or a
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synthesis and characterization techniques is an asset (e.g., XRD, SEM/TEM, XPS, UV–vis). Before applying, please note that to work at McGill University, you must be both authorized to work in Canada and
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microscopy tools such as SEM/EDX, FIB and TEM. Also use dimensional metrology for metal loss evaluation. Thermodynamics calculations using FactSage software will also be used. The candidate will be based
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utilise (where necessary), radioactive materials handling facilities, advanced materials characterisation techniques such as scanning electron microscopy (SEM), Transmission electron microscopy (TEM) and X
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Spectroscopy (ICP-OES), Scanning Electron Microscopy (SEM), gas chromatography with mass spectrometry (GC-MS), and magnetic permeametry. There will also be the option to use process modelling tools such as Aspen
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by different means (FTIR, UV-Vis, electron microscopies, TGA, NMR, EPR and elemental analysis, among others). Morphological characteriztion electron microscopy, (SEM, TEM, etc...), DLS, etc. Determine
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into functional systems. Technical Skills: Advanced analytical techniques (e.g., SEM, TEM, XPS, Raman spectroscopy). Hands-on experience with nanomaterial functionalization and coating processes. Soft Skills
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(Saint-Gobain), while a comprehensive suite of advanced micromechanical characterization methods, including optoacoustic measurements, nanoindentation, and nanoscratch testing (both in situand ex situ SEM