One or more PhD Positions in Unsupervised Learning for Medical Image Analysis

Aalborg Universitet; Denmark; On-site; DKK 360,000 - 480,000; Full time

Job summary

Aalborg Universitet søger ph.d.-studerende til forskning i usupervised learning for medicinsk billedanalyse ved Det Sundhedsvidenskabelige Fakultet. Stillingen er tre år lang og starter fra 1. november 2026 eller snarest muligt derefter.

Ansøgere forventes at have en mastergrad i et relevant felt og stærke færdigheder i maskinlæring, Python og ML-rammer. Der lægges vægt på evne til samarbejde på tværs af kliniske eksperter og ingeniørfaglige kolleger.

Qualifications

• Masterabschluss eller tilsvarende uddannelse inden for maskinlæring, datalogi eller relateret felt.
• Væsentlig erfaring med Python og ML-rammer.
• Kendskab til dyb læring, computer vision og medicinsk billedanalyse er en fordel.

Responsibilities

• Udvikle nye ML-metoder til medicinsk billedanalyse og anomaly detection.
• Samarbejde med kliniske eksperter og andre forskere ved fakultetet.
• Deltage i PhD-programmet og gennemføre relevante kursus- og forskningsaktiviteter.

Skills

Machine learning

Python

Deep learning

English

Education

Master's degree in a related field

Tools

PyTorch

TensorFlow

Job description

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One or more PhD Positions in Unsupervised Learning for Medical Image Analysis

At the Faculty of Medicine, Department of Health Science and Technology, one or more PhD stipends in Unsupervised Learning for Medical Image Analysis are available for appointment from November 1, 2026, or as soon as possible thereafter. The appointment is for a period of three years. The successful candidate will be enrolled in the PhD programme in Biomedical Engineering and Neuroscience at the Faculty of Medicine.

Who we are

The Department of Health Science and Technology (HST) at Aalborg University is an interdisciplinary research and teaching environment where engineering, medicine and health sciences come together to improve people's lives.

As a PhD fellow at HST, you will become part of an international research community with access to experienced supervisors, modern research facilities and strong interdisciplinary collaboration. You will work alongside researchers from a wide range of disciplines and engage with hospitals, industry and public-sector partners to address some of society's most important health challenges.

The department is home to approximately 180 academic staff members, around 100 PhD fellows and more than 1,700 students. We offer a stimulating research environment that encourages scientific curiosity, collaboration and professional development.

The Faculty of Medicine is committed to preparing PhD graduates for diverse career paths. Throughout your PhD, you will develop advanced research competencies alongside transferable skills that prepare you for careers in academia, industry and the public sector. Towards the end of your PhD, you will be offered dedicated career development support to help you plan your next career step.

At HST, our values – Share. Care. Dare. – shape the way we collaborate, support one another and create knowledge with societal impact.

Learn more about the department on our website and in our research portal .

Opportunistic screening envisions a scenario in which all acquired medical images are studied in minute detail to detect the early signs of any disease. When combined with AI tools, this has the potential to

• detect diseases earlier, giving the best chance of improving patient outcomes
• reduce the burden placed on radiologists and democratize diagnostic expertise to more healthcare institutions
• maximize the utility of collected radiological data

One of the major barriers to achieving this, is figuring out how to learn useful patterns in the data without relying on exhaustive labelling. For example, in the anomaly detection setting, we often assume that only healthy images are available during training. Using this, we wish to learn the appearance and structure of healthy anatomy and detect any deviation from the healthy distribution. But in the absence of labels, how should we direct the model to learn relevant features, and how can we determine which features are relevant? These questions are at the core of anomaly detection and despite being a well-established field of research, these are still very much open problems.

To this end, we are looking for candidates interested in developing new machine learning methods for medical image analysis, with a particular focus in anomaly detection and unsupervised learning. In this position, you will have the chance to explore basic machine learning research as well as more applied projects. While most of the work will involve technical machine learning research, you will also have access to clinical experts and will be expected to collaborate closely with other researchers in the Faculty of Medicine and at Aalborg University Hospital.

Applicants should have:

• A strong technical background in machine learning, computing, data science, biomedical engineering, or a related field at the level of a master degree
• Programming skills (Python) and experience with common machine learning platforms
• Experience with deep learning, computer vision, medical image analysis or unsupervised learning is an advantage.
• English language skills, both written and spoken

Qualification requirements

PhD stipends are allocated to individuals who hold a Master's degree. PhD stipends are normally for a period of 3 years. It is a prerequisite for allocation of the stipend that the candidate will be enrolled as a PhD student at the Doctoral School in Medicine, Biomedical Science and Technology in accordance with the regulations of Ministerial Order No. 1124 of September 19, 2025 on the PhD Programme at the Universities and Certain Higher Artistic Educational Institutions. According to the Ministerial Order, the progress of the PhD student shall be assessed at regular points in time. As part of the PhD study, you are among other things required to complete PhD courses corresponding to 30 ECTS, gain experience with teaching or other forms of knowledge dissemination and complete an external research stay outside of Aalborg University, preferably 3-6 months at a foreign research institution.

Further information

Read more about our recruitment process here.

Salary and terms of employment

The employment is in accordance with the Ministerial Order on the Appointment of Academic Staff at Universities and the Ministerial Order on Job Structure for Academic Staff at Universities. Furthermore, your terms of employment and salary are in accordance with the collective agreement between the Danish Confederation of Professional Associations and the state (AC collective agreement).

You can find information about the salary and salary structure for the position in the Salary Overview for Recruitment - Scientific positions (VIP ). Please refer to the introductory section of the page and the section entitled “PhD Fellow”.

There is a mutual probationary period of 3 months for the position.

Aalborg University - Knowledge for the world

Aalborg University is an international workplace with more than 3,700 employees. We offer real-world-oriented education and create world-class research results through collaboration between researchers, students, and public and private companies. This is how we achieve insights, new solutions to societal problems, and knowledge that changes the world. Our main campus is in Aalborg, but we also have campuses in Esbjerg and Copenhagen.

Aalborg University wants to reflect the surrounding society and has diversity as a core value. Therefore, everyone, regardless of personal background and orientation, is encouraged to apply for the position.