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optimal performance The PhD student will be supervised by Ida-Maria Sintorn, Professor in digital image processing, and Jens Sjölund, Assistant Professor in AI at the Department of Information Technology
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of multi-layered and 3D artworks using techniques such as terahertz imaging, thermography and ultrasonics; and (ii) integrate and visualise multimodal NDE data using data fusion, digital twins and augmented
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the subcellular to the patient level. PhD projects range from the analysis of basic cellular processes to clinical translation, from the application of novel biological approaches to the development of new imaging
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to demonstrate documented proficiency in English. You have knowledge and expertise in computer vision and/or medical image analysis, deep learning as well as mathematics. You have substantial expertise in
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range of downstream tasks. Candidates will be requested to develop novel methodologies within the artificial intelligence framework for effectively and efficiently process image time series for semantic
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imaging methodologies, biological sample preparation, vacuum technology, laser operation and optics, and electrical and mechanical engineering. Furthermore, you are expected to present your work in
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to demonstrate documented proficiency in English. You have knowledge and expertise in computer vision and/or medical image analysis, deep learning as well as mathematics. You have substantial expertise in
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experience with imaging, image processing, and/or visualization, as well as excellent programming skills. You must have a relevant Master's degree in computer science, electrical engineering, imaging science
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15th April 2026 Languages English English English We are looking for PhD Candidate in Spectral Imaging Apply for this job See advertisement This is NTNU NTNU is a broad-based university with a
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. This PhD project aims to create advanced XCT workflows by developing Artificial Intelligence (AI) and Machine Learning (ML) tools to support imaging before the reconstruction phase. The research will focus