Postdoctoral Position in Biophysical Modeling for Advanced qMRI Applications

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:	2024-12-31

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.

Key Responsibilities:

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).

Requirements:

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.

What We Offer:

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).

Location:

Radboud University, Nijmegen, The Netherlands.

Application Process:

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

For more information contact José P. Marques: jose.marques@donders.ru.nl