PhD Candidate in Explainable AI and Foundation Models for CT Imaging

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PhD Candidate in Explainable AI and Foundation Models for CT Imaging

Welcome to Maastricht University!

Do you want to contribute to advancing AI in medical imaging? In this PhD position, you will conduct research on explainable artificial intelligence and foundation models for CT imaging. You will develop and evaluate novel methods, with a strong focus on methodological innovation, rigorous validation and clinical relevance.

PhD Candidate in Explainable AI and Foundation Models for CT Imaging

Our goal: To develop novel AI methods for explainability in medical imaging, including diffusion-model-based approaches, and to advance foundation models for CT through model development, training, evaluation, and external validation.

Your colleagues: You will join the Department of Precision Medicine at Maastricht University, embedded within GROW and the Faculty of Health, Medicine and Life Sciences. You will work in an interdisciplinary environment connecting artificial intelligence, medical imaging, and clinical translation.

What you do

As a PhD candidate, you will undertake a four-year doctoral research project leading to a PhD thesis. You will develop and evaluate new methods for explainable AI in medical imaging, with particular attention to the use of diffusion models for explanation and interpretation. You will also contribute to the design, training, adaptation, and external validation of foundation models for CT images.

Are you ready to set the course for the years ahead? Then we’d love to meet you.

What you bring

We’re not looking for checkboxes; we’re interested in who you are and what you bring. Do you recognize yourself in this?

You are an analytical and curious researcher with an interest in technically innovative research at the intersection of artificial intelligence, medical imaging and clinical translation. You enjoy tackling complex problems and working in an interdisciplinary and international environment, while taking ownership of your work and developing as an independent researcher. You approach research systematically and have experience developing well-structured, well-documented and reproducible research code and organising experiments in a way that enables results to be reproduced and your work to be understood and further developed by others. You are motivated to further develop as an independent researcher and successfully complete your PhD within the appointment period.

Furthermore, you bring:

You hold, or will shortly obtain, a Master’s degree in Artificial Intelligence, Computer Science, Biomedical Engineering, Medical Image Analysis, Applied Mathematics, Data Science, or a closely related field.

You have a solid theoretical and practical background in machine learning and deep learning, including experience developing, training and evaluating models, preferably for image analysis tasks.

You have strong programming skills in Python, including the ability to develop and adapt code for machine-learning experiments, train and evaluate deep-learning models, and process and analyse experimental results. You have hands-on experience using a deep-learning framework, preferably PyTorch to develop and adapt code, train deep-learning models, and evaluate their performance.

You have knowledge of, or a strong interest in, the principles of generative modelling and an interest in applying and further developing generative approaches, including diffusion models, for medical imaging.

You have a C1 level of proficiency in written and spoken English, according to the Common European Framework of Reference for Languages (CEFR).

The following qualifications are considered advantageous:

Experience with explainable AI, uncertainty estimation, trustworthy AI, or model interpretability.

Experience with generative models, particularly diffusion models.

Experience with foundation models, self-supervised learning, representation learning, or large-scale pretraining.

Experience with medical imaging, particularly CT, and associated image formats or processing workflows.

Familiarity with DICOM, NIfTI, image registration, segmentation, or radiological image-analysis pipelines.

Experience with high-performance computing, distributed training, or working with large imaging datasets.

Experience evaluating models on heterogeneous or multi-centre data.

A master’s thesis, publication, research internship, or open-source project relevant to the position.

What we offer

At Maastricht University, you’ll work in an international, open, and engaged environment. We offer:

A 12-month contract (1,0 FTE) with the prospect of a 3 year extension based on mutual satisfaction.

A gross monthly salary between € 3.204 and € 4.051 (based on full-time employment of 38 hours per week). 8% holiday allowance and an 8.3% year-end bonus.

29 vacation days (based on full-time), four additional days off (Carnival Monday and Tuesday, Good Friday, and Liberation Day), and the possibility to accrue up to 12 extra days through compensation hours.

Freedom and space to shape your work independently and develop your ideas.

A close-knit community of colleagues to collaborate and grow with.

A solid pension plan via ABP, company fitness schemes, and access to various university sports facilities.

Access to doctoral training, scientific conferences, and opportunities to develop specialist expertise in AI and medical imaging.

Access to a strong interdisciplinary network in artificial intelligence, imaging, and precision medicine.

An inspiring work environment in the heart of Europe.

About the Faculty of Health, Medicine and Life Sciences (FHML)

FHML is committed to health in the broadest sense: from molecule to human, and from healthcare to prevention. We train healthcare professionals and researchers through innovative educational programmes and conduct groundbreaking research in health and well-being. As part of Maastricht UMC+ (MUMC+), our international and interdisciplinary community forms a unique collaboration between university and academic hospital, where education, research, and care come together.

About the Department Precision Medicine

The Department of Precision Medicine is embedded within the GROW research institute and the Faculty of Health, Medicine and Life Sciences at Maastricht University. Within the department, the D-Lab focuses on AI-based decision-support systems and the advanced analysis of medical data and images.

Interested?

Want to know more about this position or what it’s like to work at our university? Reach out to Zohaib Salahuddin via z.salahuddin@maastrichtuniversity.nl or to Sina Amirrajab via sina.amirrajab@maastrichtuniversity.nl. The deadline for submitting your application is 15 September 2026.

If you are interested, please submit the following:

A motivation letter explaining your interest in the project and your relevant background.

Your curriculum vitae.

Copies of your bachelor’s and master’s degree transcripts.

Contact details of two referees.

Where applicable, links to relevant publications, your master’s thesis, code repositories, or other research outputs.

The preferred starting date for this position is 1 November 2026, or as soon as possible thereafter.

Apply now via the button below. We look forward to getting to know you!

About Maastricht University

At Maastricht University, we collaboratively seek solutions to help move the world forward. We do this with 23,300 students and 5,400 employees across 5 regional locations, 6 faculties, and more than 70 research institutes. We encourage you to push boundaries and discover new opportunities for yourself and the world around you. Together, we can find the answers for tomorrow.

The vacancy is open for internal and external candidates. In case of equal qualifications, internal candidates will be prioritized.

At Maastricht University, we prefer to contact potential candidates directly. We therefore kindly ask that no agencies or intermediaries submit offers or approaches.

Maastricht University is committed to promoting and nurturing a diverse and inclusive community. We believe that diversity in our staff and student population contributes to the quality of research and education at UM, and strive to enable this through inclusive policies and innovative projects led by teams of staff and students. We encourage you to apply for this position.

Job Type: Academic

Faculty/Service Center: Faculty of Health, Medicine and Life Sciences

Closing date: 15-09-2026

FTE min: 1,0

FTE max: 1,0

Salary min: €3204,00

Salary max: €4051,00

ID job: 3738

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Job Type: Academic

Faculty/Service Center: Faculty of Health, Medicine and Life Sciences

Closing date: 15-09-2026

FTE min: 1,0

FTE max: 1,0

Salary min: €3204,00

Salary max: €4051,00

ID job: 3738

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