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PhD Candidate in Spectral Imaging

Colourlab, Department of Computer Science, NTNU (Gjøvik Campus)

About the position:

Within the UNVEIL project, the individual research project associated with this position (DC7) is entitled Multiscale and multimodal spectral image acquisition, integration, analysis and visualization.

Objectives: This project will develop strategies for the acquisition, integration, analysis and visualisation of spectral images, for scientific analysis of wall paintings. The data for this study will come from various multispectral/hyperspectral imaging technologies, covering various spectral ranges, such as VNIR, SWIR, and MWIR. Based on these heterogeneous datasets, spectral libraries with an extended spectral range will be generated and used for material mapping and classification, employing multivariate analysis (MVA) and advanced data-driven approaches, including artificial intelligence (AI) methods. The material mapping results will be validated using complementary analytical techniques applied to the same artworks. In addition, style characterization of the paintings will be conducted by extracting both local and global features, such as texture, brushstrokes, cracks, and other surface patterns. This will support the study of artists’ techniques, enable enhanced visualization, and facilitate change monitoring over time. The project will also develop a visualization architecture for presenting multiscale and multirange hyperspectral datasets, tailored to the needs of different user groups including conservation professionals. The fused HSI data will be applied to investigate painting stratigraphy and to detect superficial as well as subsurface disorders, supporting improved understanding of the artworks’ condition and conservation needs.  

Expected Results: 1) Multimodal and multiscale spectral imaging framework, including acquisition methodology, data architecture, analysis, visualisation tool 2) A new method for mapping materials (substrate, pigments, binders...) from spectral image data and a combination of traditional material/imaging models and modern ML-based approaches; 3) Spectral library of painting materials over VNIR-SWIR-MWIR ranges  

Key exploitable results (KER): Open-source software suite for material mapping based on multimodal-multiscale spectral imaging

Required selection criteria:

• You must have 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 or equivalent. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been obtained at master's level. Master students can apply, but the master's degree must be obtained and documented before starting the position and no later than October 1, 2026

• At the date of recruitment, you must NOT have been awarded a doctoral degree.

• You must have a strong academic background from your previous studies and have an average grade from your Master's degree study, or equivalent education, which is equal to B or better compared to NTNU's grading scale. If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you have a weaker grade background, you may be considered if you can document that you are particularly suitable for a PhD education.

• You must meet the requirements for admission to the faculty's Doctoral Programme in computer science.

• Excellent oral and written communication skills in English.

• You must comply with the MSCA mobility rule: you must not have resided or carried out your main activity (work, studies, etc.) in the country of the recruiting organisation for more than 12 months in the 36 months immediately before recruitment (short stays such as holidays are not taken into account).

Complete job advertisement and application submission here: https://www.jobbnorge.no/en/available-jobs/job/298131/phd-candidate-in-spectral-imaging

Application deadline: 15.04.2026