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20th March 2026 Languages English English English The Department of Circulation and Medical Imaging has a vacancy for a PhD Candidate in Artificial Intelligence and Medical Imaging Apply
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and Technology (NTNU) for general criteria for the position. Preferred selection criteria Documented competence within X-ray imaging, diffraction or electron microscopy, preferably transmission
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and Technology (NTNU) for general criteria for the position. Preferred selection criteria Documented competence within X-ray imaging, diffraction or electron microscopy, preferably transmission
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systems to reason more coherently about ship designs, reducing ambiguity in the data available to machine‑learning systems, and supports explainability by grounding AI outputs in a known structure. This
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the semantic foundation that enables AI systems to reason more coherently about ship designs, reducing ambiguity in the data available to machine‑learning systems, and supports explainability by grounding AI
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standard-grounded assurance principles into a coherent theoretical structure. The PhD candidate will conduct fundamental research on how monitoring information can be used to evaluate adaptive learning
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of optical diagnostics, such as: Near and far field high-speed microscopic imaging. Chemiluminescence-based techniques. Schlieren imaging and shadowgraphy. These tools will be used to obtain high-resolution
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field high-speed microscopic imaging. Chemiluminescence-based techniques. Schlieren imaging and shadowgraphy. These tools will be used to obtain high-resolution insights into fuel–air mixing, spray break
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advanced phenotyping, imaging technologies, AI-based analyses, and digital twins. The PhD candidate will work on spring wheat genotypes adapted to Norwegian and northern European growing conditions
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using stem cell differentiation. The interaction between these cell types will be studied in co-culture and characterized using live-cell imaging, transcriptomic and proteomic profiling