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laboratory analytical methods (e.g., chromatography, mass spectrometry). Familiarity with AI or machine learning applications relevant to environmental data analysis. Basic knowledge of GIS/mapping tools
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related field. Demonstrated expertise in machine learning, deep learning, or advanced statistical analysis applied to complex, multimodal data. Hands-on experience with high-performance computing (HPC
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/ deep learning workflows) and integrate these readouts with viability metrics and genomic data. Collaborate closely with clinicians, surgeons and SINTEF partners on patient sample handling, experimental
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pressure-build ups in potential multi-site storage licenses. The research will help to suggest best practices for machine learning integration in de-risking CO2 storage sites. We seek a candidate with a