Postdoctoral Position in Biophysical Modeling Advanced qMRI

This position is part of a project focused on developing efficient and robust models to extract quantitative biomarkers from MRI data, aiming to accelerate and enhance clinical applications in neurodegenerative, neuro-inflammatory, and neurovascular diseases.

The selected candidate will lead the development and integration of neural network decoding strategies for Multi-Compartment Relaxometry (MCR) and Myelin Water Imaging (MWI) as a new tool for assessing brain tissue microstructure. The work will focus on enhancing computational efficiency, improving biomarker extraction, and expanding the biophysical models to include vascular tissue factors.

Job type:
Postdoc

Job location:

Radboud University, Nijmegen, The Netherlands.

Deadline:

We are seeking a highly motivated Postdoctoral Researcher to join our interdisciplinary team working on cutting-edge biophysical modelling for myelin water imaging (MWI) and quantitative MRI techniques. This position is part of a project focused on developing efficient and robust models to extract quantitative biomarkers from MRI data, aiming to accelerate and enhance clinical applications in neurodegenerative, neuro-inflammatory, and neurovascular diseases.

The selected candidate will lead the development and integration of neural network decoding strategies for Multi-Compartment Relaxometry (MCR) and Myelin Water Imaging (MWI) as a new tool for assessing brain tissue microstructure. The work will focus on enhancing computational efficiency, improving biomarker extraction, and expanding the biophysical models to include vascular tissue factors.

• Develop and optimize neural network-based methods for MCR-MWI and Diffusion Informed MWI.
• Collaborate with other team members to test and apply these models to data from different MRI systems and field strengths (1.5T, 3T, 7T).
• Lead efforts to develop biomarkers beyond Myelin Water Fraction (MWF), incorporating new data related to tissue vascularization and metabolic oxygen rates (CMRO2).

• PhD in physics, biomedical engineering, medical imaging, computer science, or a related field.
• Expertise in MRI data analysis, biophysical modeling, and/or neural networks.
• Strong programming skills (Python, MATLAB, or similar) and experience with machine learning techniques.
• Familiarity with MRI pulse sequences and quantitative MRI methods (such as DWI, MWI or QSM) is highly desirable.

• An exciting research environment within Radboud University, Nijmegen, one of the leading institutions in neuroimaging, where a 14T human scanner will soon be installed.
• Access to state-of-the-art MRI facilities and computational resources.
• Opportunities for professional development in postdoctoral program and collaboration with international partners (Kwok-shing Chan - MGH).

Radboud University, Nijmegen, The Netherlands.

Applications will open formally in mid-october. A CV, cover letter and contact information for two references.