7 Tesla MRI provides unprecedented means to study anatomical structures in vivo. This is of
particular interest for the hippocampus which has a complex internal structure composed of
intricated layers with different cellular composition. 7 Tesla MRI with very high spatial
resolution and multi-contrast imaging (T1, T2, R2*, QSM…) has the potential to precisely map
the internal architecture of the hippocampus, resulting in new biomarkers of pathologies such
as epilepsy and Alzheimer’s disease. However, these advances in image acquisition require
corresponding advances in image analysis to be fully exploited. To that purpose, we propose
a new approach to move computational anatomy beyond morphometry by integrating both
multi-contrast MRI and shape into a single framework. These mathematical and
computational approaches are expected to significantly advance the field of computational
anatomy of the human brain, breaking down the millimeter barrier of conventional brain
morphometry and providing a coherent analysis framework for anatomical data at ultra-high
spatial resolution.

The position is offered within a 3-year USA-France collaborative project involving the ARAMIS
Lab (Paris, France), Ecole Normale Supérieure (Cachan, France), Neurospin (Saclay, France)
and the Center for Magnetic Resonance Research at University of Minnesota (Minneapolis, USA).

Your profile:
- PhD in the field of medical image computing
- Previous research work on at least one of the following topics: registration, geometrical
modeling, segmentation, shape analysis
- Good relational and communication skills to interact with professionals from various
backgrounds.

Starting date: from January 2017
Duration: 2 to 3 years
Salary: to be negotiated depending on experience
Ready to take up the challenge?
send your CV to or to