Postdoc position
Project abstract:
Learning is a brain network phenomenon thought to arise from synergistic interactions between
multiple brain regions. Although central, this hypothesis has never been fully tested, yet. Indeed,
progress has been limited by the lack of approaches for studying brain interactions beyond
pairwise relations, the so-called higher order interactions (HOIs). Our objective is to build a
theoretical and data analysis framework to demonstrate the role of HOIs in human brain networks
supporting causal learning. The Hinteract project will be composed of three scientific work
packages (WPs). WP1 will develop a novel informational theoretical approach to infer task-related
(functional) HOIs from neural time series and will characterise HOIs supporting causal learning
using a multiscale dataset including magnetoencephalography (MEG) and intracranial
stereo-electroencephalography (SEEG) data. WP2 will develop a network science formalism to
analyse the structure and dynamics of functional HOIs patterns, and it will characterise the
hierarchical organisation of learning-related HOIs inferred in WP1. WP3 will compile and share the
neuroinformatics tools developed in the project and it will make it interoperable with the EBRAINS
infrastructure. Overall, our project will reveal whether causal learning is supported by cerebral
HOIs, and produce a theoretical and computational framework for the study of HOIs in brain
networks that will be shared with the scientific community.
Workpackages:
WP1: Inference of learning-related high-order interactions in the brain
WP2: Analysis of learning-related high-order interactions in the brain using network science approaches
WP3: Integrated neuroinformatics tools for HOI analysis and sharing on EBRAINS infrastructure
The hired postdoctoral researcher will mainly work on WP2, i.e., on the development of new formalisms and methods to apply to
higher order interaction patterns identified in the data analyzed in WP1.
We are looking for a candidate with a strong background in statistical physics, complex networks, computational tools and programming, and
a strong interest in interdisciplinary work. Having already worked on higher order networks is a plus but not required.
The hired postdoctoral researcher will be based in the CPT on the Luminy Campus (south of Marseille) but will also devote a significant part of their time
at the INT in the La Timone campus.
Position starting date: October 1st, 2024 (negotiable)
Duration of the position: 1 year, renewable
Deadline for applications: June 5, 2024
TO APPLY:
- please send CV and motivation letter, and
- have your supervisors send directly two letters of recommendation,
within June 5, 2024 to
alain.barrat @ cpt.univ-mrs.fr
and
andrea.brovelli @ univ-amu.fr
