DTU Compute is excited to offer a PhD position for a talented and motivated student to join the research activities led by Marco Pizzolato. These activities involve the development of advanced AI methods for describing the physical properties of the signal we collect using Diffusion Magnetic Resonance Imaging. This is an exciting opportunity to do research at the forefront of medical imaging, mathematical modeling, and AI.
Responsibilities and qualifications
The focus of this position is to push the boundaries of Microstructural biophysical modeling of diffusion-weighted MRI data by means of advanced AI methods. The goal is to obtain imaging biomarkers to help understand and diagnose diseases of the tissue with, at least initially, a focus on the human brain.
You will be a vital part of the Visual Computing section , supervised by Marco Pizzolato . You will also be an integral part of the Microstructure And Plasticity group, a dynamic, multi-disciplinary, and inter-departmental research group that strives to study the brain with different imaging modalities.
Your primary tasks will be to:
Conduct research and develop methods for microstructural modeling with Diffusion MRI including aspects like MRI acquisition, modeling/representation, diffusion physics simulation, probabilistic inference methods, machine learning, and deep learning.
Publish research findings in leading international conferences and journals.
Assist in the supervision of MSc and BSc student projects in related fields.
Manage your own academic research and administrative duties, including small-scale project management, to ensure various tasks meet deadlines.
Selection Criteria
A two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree in computer science, bio/medical-informatics or engineering, mathematics, physics, electrical engineering or closely related fields.
A strong background in modeling for Magnetic Resonance Imaging, preferably in Diffusion MRI, or at least a strong desire to make it the primary research focus.
A strong background in machine learning, explainable AI, and deep learning.
Good foundations in mathematics are desired (e.g., concepts like orthogonal functions, etc.).
Software and debugging skills in Python (web development is a plus), experience with learning frameworks such as PyTorch, deploying computations to multiple CPUs/GPUs and remote servers, experience with Linux and development tools such as git and conda.
Ability to manage own academic research and associated activities.
Excellent communication skills and ability to work in interdisciplinary teams.
Publication records are highly desired.
You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.
Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education .
Assessment
The assessment of the applicants will be made by Marco Pizzolato.
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 appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union.
The period of employment is 3 years. Starting date is 1 January 2026 or according to mutual agreement. The position is a full-time position.
You can read more about career paths at DTU here http://www.dtu.dk/english/about/job-and-career/working-at-dtu/career-paths.
Further information
For more information, please contact Associate Professor Marco Pizzolato (mapiz@dtu.dk ) or Head of Section, Professor Anders Bjorholm Dahl (abda@dtu.dk ).
You can read more about the Section for Visual Computing at DTU Compute -Visual Computing and previous research at https://orbit.dtu.dk/en/persons/marco-pizzolato (and links therein).
If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark . Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar ” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.
Application procedure
Your complete online application must be submitted no later than 6 November 2025 (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:
A letter motivating the application (cover letter)
Curriculum vitae
Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale
In the CV, please name up to 2 people who may be contacted to provide reference letter (e.g. master thesis supervisor)
You may apply prior to obtaining your master's degree but cannot begin before having received it.
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
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. Read more about us at www.compute.dtu.dk .
Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.