PhD Project in Mathematical Image Analysis for Sustainable Materials

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Job summary

University of Copenhagen invites applications for a PhD project in mathematical image analysis for sustainable materials. The position is within the IMAGE section and involves interdisciplinary collaboration with LU/DTU researchers to develop interpretable, structure-aware descriptors for materials data.

We seek candidates with strong mathematical background and experience in image analysis, ML or scientific computing, and a solid interest in quantitative, benchmarked methods for visual

Qualifications

• Strong mathematical grounding and interest in quantitative image-based characterisation.
• Experience with ML, image analysis, scientific computing or data science is advantageous.
• Focus on understanding, benchmarking and developing methodology around visual representations.

Responsibilities

• Carry through an independent research project under supervision.
• Complete PhD courses corresponding to about 30 ECTS / ½ FTE.
• Participate in active research environments, including stays at other institutions.
• Engage in teaching and knowledge dissemination activities.
• Publish papers in high-impact journals and defend the PhD thesis.

Skills

Mathematical maturity

Machine learning

Image analysis

Data science

Python programming

Education

Master’s degree in related field

Job description

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PhD Project in Mathematical Image Analysis for Sustainable Materials

The project

This position focuses on sustainable materials, including fibre‑based materials, porous systems, and metals, where structural organisation across scales determines key material properties. The project is carried out in close collaboration with domain experts in LU who formulate scientific questions related to how production conditions and usage influence material performance. The project does not focus on developing new foundation‑model architectures, but on understanding, evaluating, and exploiting learned representations for scientific image analysis. The developed methods will be used to investigate how manufacturing and usage affect material structure and performance.

At the University of Copenhagen, the project contributes to RAPTOR through benchmarking, modelling, and analysis. In this context, the successful candidate will develop methods for quantitative structural characterisation of complex materials, with an emphasis on approaches that do not rely exclusively on segmentation. In particular, the work will explore structure‑aware representations such as orientation fields and tensor‑based descriptors, enabling robust analysis of heterogeneous and fibrous materials, and in close collaboration with the domain experts, the work will focus on identifying what matters from the analysis to inform the domain experts about the material and how the next experiment should be formed.

The candidate will take part in the development and applications of methods to evaluate how RAPTOR representations perform on relevant analysis tasks, using well‑defined benchmarks and comparisons to established approaches. Further, the candidate will take part in the development of concise, interpretable models that relate material structure to key properties, with a focus on robust and practical descriptors. The project will deliver validated analysis methods, benchmark tasks, and structural descriptors, developed in close collaboration with materials scientists and tested on real‑world data.

Who are we looking for?

We are looking for candidates within the field(s) of Computer Science, Mathematics, Physics, Engineering etc. Applicants should have solid mathematical maturity and an interest in developing, analysing, and evaluating quantitative methods for image‑based characterisation of complex structures. Experience with machine learning, image analysis, scientific computing, or data science is advantageous, but the project focuses on understanding, benchmarking, and developing methodology around visual representations rather than on large‑scale deep‑learning model development.

Our group and research‑and what do we offer?

The project is supervised by Jon Sporring (UCPH), Anders Bjorholm Dahl (DTU), Stephen Hall (LU), and Martin Bech (LU), combining expertise in mathematical image analysis, computer vision, quantitative imaging, X‑ray imaging, and materials science. The student will have opportunities to collaborate with researchers at UCPH, DTU, LU, and international imaging infrastructures, and to contribute to open‑source research software and datasets.

The candidate will join the IMAGE section at the University of Copenhagen, an active research group working on image analysis, computer vision, geometry, computational modelling, and AI. The section is closely connected to QIM, Danish BioImaging, Euro‑BioImaging, the Human Organ Atlas, and the Pioneer Centre for AI, providing access to leading imaging infrastructures, large‑scale datasets, and broad interdisciplinary collaborations.

IMAGE offers a friendly, collaborative, and informal research environment with close interaction between faculty, postdoctoral researchers, and PhD students. We value curiosity, mathematical depth, openness, and teamwork, and provide a supportive setting for developing independent research careers.

• Principal supervisor is Professor, Jon Sporring, Department of Computer Science, [e-mail], [phone]

The PhD programme

Depending of your level of education, you can undertake the PhD programme as either:

Option A: A three‑year full‑time study within the framework of the regular PhD programme (5+3 scheme), if you already have an education equivalent to a relevant Danish master’s degree.

Option B: An up to five‑year full‑time study programme within the framework of the integrated MSc and PhD programme (the 3+5 scheme), if you do not have an education equivalent to a relevant Danish master´s degree – but you have an education equivalent to a Danish bachelors’ degree.

Qualifications Needed For The Regular Programme

To be eligible for the regular PhD programme, you must have completed a degree programme, equivalent to a Danish master’s degree (180 ECTS/3 FTE BSc + 120 ECTS/2 FTE MSc) related to the subject area of the project, e.g. [relevant educations]. For information of eligibility of completed programs, see General assessments for specific countries and Assessment database.

Terms of employment in the regular programme

Employment as PhD fellow is full time and for maximum 3 years.

Employment is conditional upon your successful enrolment as a PhD student at the PhD School at the Science, University of Copenhagen. This requires submission and acceptance of an application for the specific project formulated by the applicant.

The position is covered by the Memorandum on Job Structure for Academic Staff.

Salary, pension and other conditions of employment are set in accordance with the Agreement between the Ministry of Taxation and AC (Danish Confederation of Professional Associations) or other relevant organisation. Currently, the monthly salary starts at 31,800 DKK/approx. 4,200 EUR (August 2026‑level). Depending on qualifications, a supplement may be negotiated. The employer will pay an additional 18,07 % to your pension fund.

Foreign and Danish applicants may be eligible for tax reductions, if they hold a PhD degree and have not lived in Denmark the last 10 years.

Qualifications Needed For The Integrated MSc And PhD Programme

If you do not have an education equivalent to a relevant Danish master´s degree, you might be qualified for the integrated MSc and PhD programme, if you have an education equivalent to a relevant Danish bachelor´s degree. Here you can find out, if that is relevant for you: General assessments for specific countries and Assessment database.

Terms of the integrated programme

To be eligible for the integrated scholarship, you are (or are eligible to be) enrolled at one of the faculty’s master programs in Computer Science.

Students on the integrated programme will enroll as PhD students simultaneously with completing their enrollment in this MSc degree programme.

The duration of the integrated programme is up to five years, and depends on the amount of credits that you have passed on your MSc programme. For further information about the study programme, please see: www.science.ku.dk/phd, “Study Structures”

Until the MSc degree is obtained, (when exactly two years of the full 3+5 programme remains), the grant will be paid partly in the form of 48 state education grant portions (in Danish: “SU‑klip”) plus salary for work (teaching, supervision etc.) totaling a workload of 150 working hours per year.

A PhD grant portion is currently (2026) DKK 7.426 before tax.

When you have obtained the MSc degree, you will transfer to the salary‑earning part of the scholarship for a period of two years. At that point, the terms of employment and payment will be according to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State (AC). The position is covered by the Protocol on Job Structure.

Responsibilities and tasks in both PhD programmes

• Complete and pass the MSc education in accordance with the curriculum of the MSc programme (ONLY when you are attending the integrated MSc and PhD programme)
• Carry through an independent research project under supervision
• Complete PhD courses corresponding to approx. 30 ECTS / ½ FTE
• Participate in active research environments, including a stay at another research institution, preferably abroad
• Teaching and knowledge dissemination activities
• Write scientific papers aimed at high‑impact journals
• Write and defend a PhD thesis on the basis of your project

We Are Looking For The Following Qualifications

• A strong academic background in computer science, applied mathematics, engineering, physics, statistics, or a related field.
• Experience with image analysis, computer vision, scientific computing, statistics, applied mathematics, machine learning, or related quantitative methods.
• Relevant publications, project work, or thesis experience.
• Programming experience, preferably in Python or similar scientific computing environments.
• A curious and analytical mindset with a strong interest in mathematical image analysis, quantitative imaging, and the evaluation of visual representations.
• An interest in developing interpretable and scientifically meaningful methods at the interface between computer science and materials science.
• Good written and spoken English skills.

The further process

After deadline, several applicants will be selected for academic assessment by an unbiased expert assessor. You are notified whether you will be passed for assessment.

The assessor will assess the qualifications and experience of the shortlisted applicants with respect to the above‑mentioned research area, techniques, skills and other requirements. The assessor will conclude whether each applicant is qualified and, if so, for which of the two models. The assessed applicants will have the opportunity to comment on their assessment. You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/.

Questions

For specific information about the PhD fellowship, please contact the principal supervisor.

General information about PhD study at the Faculty of SCIENCE is available at the PhD School’s website: https://www.science.ku.dk/phd/

The University of Copenhagen wishes to reflect the surrounding community and invites all regardless of personal background to apply for the position.

Part of the International Alliance of Research Universities (IARU), and among Europe’s top‑ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.

Contact

Jon Sporring
E‑mail: [e-mail]

Application deadline: 06-08-2026

Employment start: 01-12-2026

Working hours: Full time

Department/Location: Department for Computer Science

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