PhD in Explainable AI for CT Imaging & Foundation Models

EURAXESS Ireland; Maastricht; Hybrid; EUR 36,000 - 45,000; Full time

Benefits offered by this job

Contract extension

Gross salary €3,204–€4,051/month

8% holiday allowance

ABP pension

Fitness facilities

Doctoral training

International environment

Job summary

Maastricht University invites applications for a PhD Candidate position focused on explainable AI and foundation models for CT imaging. You will develop novel AI methods, validate them rigorously, and bring clinical relevance to imaging research.

Join the Department of Precision Medicine within GROW and the Faculty of Health, Medicine and Life Sciences, working at the intersection of AI, medical imaging, and clinical translation.

Qualifications

• Master’s degree in AI/CS/ Biomedical Engineering, Medical Image Analysis, Applied Mathematics, Data Science, or closely related field.
• Solid theoretical and practical background in machine learning and deep learning, including experience developing, training and evaluating models for image analysis.

Responsibilities

• Undertake a four-year doctoral research project leading to a PhD thesis.
• Develop and evaluate new methods for explainable AI in medical imaging, with diffusion models for explanation and interpretation.
• Contribute to design, training, adaptation, and external validation of foundation models for CT images.

Skills

Python

PyTorch

Deep learning

Explainable AI

Medical imaging

CEFR C1 English

Education

Master’s degree in AI/CS/ Biomedical Engineering/ Medical Imaging

Tools

PyTorch

Python

Diffusion models

NIfTI

DICOM

Job description

Maastricht University invites applications for a PhD Candidate position focused on explainable AI and foundation models for CT imaging. You will develop novel AI methods, validate them rigorously, and bring clinical relevance to imaging research.

Join the Department of Precision Medicine within GROW and the Faculty of Health, Medicine and Life Sciences, working at the intersection of AI, medical imaging, and clinical translation.