PhD Position F/M PhD F/H Shape analysis of microstructure-augmented whiter matter fascicles

Contract type : Fixed-term contract

Level of qualifications required : Graduate degree or equivalent

Fonction : PhD Position

About the research centre or Inria department

The Inria Centre at Rennes University is one of Inria's nine centres and has more than thirty research teams. The Inria Centre is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative PMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc.


Magnetic resonance imaging (MRI) and in particular diffusion MRI (dMRI) provide detailed information about the macroscopic organisation of brain white matter (WM) fiber bundles (see Figure), with a method called fiber tractography. Complementary to the geometry of fibers, dMRI is also sensitive to the microscopic tissue structure and its alteration with pathology. The joint analysis of white matter fascicles and their associated microstructure organisation requires the development of specific mathematical representations.


The main objective of this thesis will be the development of mathematical models of microstructure-augmented fascicle (MAF), which convey both the macro-structural information provided by tractography and the microstructural information provided by the diffusion models along the WM fascicles. In the context of the PASTRAMI (**Pa**tient-specific **s**tatistics for micros**tr**ucture-**a**ugmented connecto**mi**cs) collaborative project (funded by the PRC program, agence nationale de la recherche, 2023-2028), these representations will be used to derive patient-specific biomarkers of functional recovery in patients suffering from severe traumatic brain injury.

Main activities

We will develop upon a shape analysis frameworks such as the LDDMM (Large Diffeomorphic Metric Mapping) framework that relies on Riemannian geometry and is well adapted to the study of anatomical structures, to construct the models for the representation of fiber bundles (which can be defined as 1-dimensional curves or 2-dimentional surfaces in R3) and their associated microstructure. In continuation, we will also analyse the brain connectome, which represents the network of connected gray matter regions in the brain. We will build upon methods developed for the analysis of graphs with complex data.


We look for candidates strongly motivated by challenging research topics in neuroimaging. The applicant should present a good background in applied mathematics. Basic knowledge in image processing would be a plus. Good knowledge of computer science aspects is also mandatory, especially in Python and C++.

Benefits package

  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Possibility of teleworking (90 days per year) and flexible organization of working hours
  • Partial payment of insurance costs


Monthly gross salary amounting to 2100 euros for the first and second years and 2190 euros for the third year