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PhD Candidate in Shape Analysis of Microstructure-Enhanced White Matter Fascicles
Il y a 3 mois
Position Overview and Benefits
The field of magnetic resonance imaging (MRI), particularly diffusion MRI (dMRI), offers intricate insights into the macroscopic structure of brain white matter (WM) fiber bundles through a technique known as fiber tractography. In addition to the geometric characteristics of fibers, dMRI is sensitive to the microscopic tissue architecture and its variations due to pathological conditions. The comprehensive examination of white matter fascicles alongside their corresponding microstructural organization necessitates the formulation of specialized mathematical models.
Assigned Responsibilities
The primary aim of this doctoral research will be to create mathematical frameworks for microstructure-augmented fascicles (MAF), which integrate both the macro-structural data derived from tractography and the microstructural insights provided by diffusion models along the WM fascicles. Within the scope of the PASTRAMI (**Pa**tient-specific **s**tatistics for micros**tr**ucture-**a**ugmented connecto**mi**cs) collaborative initiative, funded by the national research agency, these models will be instrumental in deriving patient-specific biomarkers that indicate functional recovery in individuals experiencing severe traumatic brain injuries.
Key Activities
We will enhance shape analysis methodologies, such as the LDDMM (Large Diffeomorphic Metric Mapping) framework, which is grounded in Riemannian geometry and is particularly suited for investigating anatomical structures. This will facilitate the development of models for representing fiber bundles, defined as one-dimensional curves or two-dimensional surfaces in R3, along with their associated microstructure. Furthermore, we will explore the brain connectome, which illustrates the network of interconnected gray matter regions within the brain, utilizing techniques developed for analyzing complex data graphs.
Required Skills
We seek candidates who are deeply passionate about tackling challenging research questions in neuroimaging. Applicants should possess a solid foundation in applied mathematics. Familiarity with image processing techniques would be advantageous. Proficiency in computer science, particularly in Python and C++, is essential.
Benefits
- Partial reimbursement of public transport costs for commuting.
- Subsidized meals.
- Partial coverage of health insurance expenses.
- Opportunity for remote work (up to 90 days annually) and flexible working hours.
Compensation
The gross monthly salary will be €2,100 for the first two years and €2,190 for the third year.
