Postdoc in Practical AI-based Reconstruction for High-throughput CT of Natural History Samples - DTU Compute

Are you excited by developing novel computational imaging methods that move from research into real-world use? Join our interdisciplinary team as a postdoc to develop advanced image reconstruction algorithms for a novel robotic computed tomography system that will transform how natural history collections are digitized and studied. You will have the opportunity to conduct high-impact research in computational imaging and AI, contribute to widely used open-source software, collaborate with leading researchers in physics and natural history, and publish your work while helping build technology with lasting scientific impact.

Responsibilities and qualifications
We are looking for a highly motivated early-career researcher in advanced image reconstruction methods to join our imaging research group and project “Natural Heritage 3D”. This collaborative project between Visual Computing @ DTU Compute, DTU Physics, Copenhagen University, and the Natural History Museum aims to develop a fully automated robotic computed tomography system along with computational methods to enable 3D digitization of large collections of natural history specimens.

The Natural History Museum has millions of natural specimens collected over 400 years, which provide an enormous source of information on natural history. CT scans provide a unique method to visualize internal features in 3D in a fully non-destructive manner. In an effort towards digitizing collections and unlocking hidden information on an unprecedented scale, an automated CT system is being developed to scan and analyse large quantities of such specimens. Selected science cases include seal and polar bear craniums as well as snakes and lizards preserved in alcohol.

In addition to experimental CT scan equipment, a key component is the computational pipeline to turn acquired CT projections through reconstruction and image analysis into digital volumes and extract relevant quantitative data. Given the large quantities of specimens, scanning needs to be fast and automated, which demands state-of-the-art reconstruction and analysis methods to handle the data arising from very fast scans taken with few and noisy projections. The focus of this postdoc position is the reconstruction step, conducting research and developing suitable image reconstruction methods to produce sufficiently high-quality 3D volumetric images of natural heritage specimens from the robotic CT system at the DTU 3D Imaging Center.

Your primary activities include:

• Develop new mathematical methods for fast reconstruction of CT data from fast (e.g. sparse-view and/or high-noise) data.
• Develop and validate numerical implementations on simulated and real CT data.
• Explore and compare supervised and self-supervised machine learning/AI-based reconstruction methods with optimization/regularization-based as well as filtered back-projection reconstruction methods.
• Contribute to the development and validation of practical computational reconstruction pipelines for a new fast robotic computed tomography system in the DTU 3D Imaging Centre in collaboration with scientific software developers.
• Contribute to and be part of open-source scientific software communities around the Core Imaging Library and qim3D packages.
• Publish scientific articles within computational methods, data, and applications in collaboration with colleagues in physics and natural history.

This role is part of the QIM Center for Quantification of Imaging Data (/). As part of QIM, you will be interacting with a large imaging network in connection with large-scale facilities such as MAX IV, ESS, DTU 3D Imaging Center, and other facilities internationally. In conjunction with research and open-source software development, the role involves tasks in relation to the QIM Center, including participating in and contributing to training and hackathon events, interacting with users, helping with event organization, etc. From experience, this enables involvement in strong collaborative research projects on both theoretical and practical imaging problems and a pathway to impact of the computational methods developed.

Strong candidates for this position are expected to have:

• a PhD degree in computational imaging, ideally X-ray CT reconstruction
• experience developing deep learning and/or regularization-based image reconstruction methods
• experience with scientific Python programming
• experience handling both simulations and large real data
• strong spoken and written communication skills in English
• strong collaboration skills as well as being self-driven.

As a formal qualification, you must hold a PhD degree (or equivalent). If you are close to completing a PhD degree, your application must include a written statement from your main supervisor confirming that you are expected to complete the PhD.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and terms of employment
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. In addition, supplements can be negotiated in accordance with DTU’s salary structure for scientific staff:

The period of employment is 2 years. Starting date is expected to be 1. November 2026 or soon thereafter. The position is full-time.

You can read more about career paths at DTU here .

Further information
Further information may be obtained from Associate Professor Jakob Sauer Jørgensen ( Se e-mailadresse på jobbank.dk ), Department of Applied Mathematics and Computer Science, Technical University of Denmark.

You can read more at .

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark .

Application procedure
Your complete online application must be submitted no later than 15 September 2026 (23:59 Danish time) .

Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file . The file must include:

• Motivated application (cover letter)
• CV
• Academic Diplomas (MSc/PhD – in English)
• List of publications
• Link to examples of scientific code developed by the applicant (for example GitHub link)

Applications received after the deadline will not be considered.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position.

DTU Compute – Department of Mathematics and Computer Science – is an internationally recognised academic environment with over 400 employees and 10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus on ensuring that our research results contribute to creating a better society by supporting areas such as health, green transition, energy supply, and life science. We collaborate with universities, public and private organisations, and companies in Denmark and abroad, and through DTU’s startup ecosystem, we encourage innovation and entrepreneurship. We have a strong ethical, human, and sustainable approach that ensures integrity in our work. Therefore, we strive for and take responsibility for driving the democratisation of digital technologies, so that everyone has the opportunity to actively participate in the development, and we ensure a continued open, democratic, and inclusive society for the benefit of all. At DTU Compute, we value diversity, inclusion, and a flexible work-life balance.

DTU – For the benefit of society since 1829
DTU is one of Europe's leading elite technical universities. Through research and education at an international top level, we create solutions to the major societal challenges of our time and help secure Europe's global leadership in sustainable technological development. Since Hans Christian Ørsted founded DTU almost 200 years ago, our mission has remained the same: We develop and create value through the natural and technical sciences for the benefit of society. DTU has 13,800 students, 1,600 PhD students, and 6,500 employees. We work in an international environment and have an inclusive, stimulating, and informal work culture. DTU has campuses in all parts of Denmark and in Greenland and collaborates with the best universities around the world.

Location
Kgs. Lyngby, Denmark

Apply Before
2026-09-15T21:59:00+00:00