Postdoctoral position

NEUROAGE

Neurocognitive aging phenotypes as emerging properties of reserve–energy dynamics

Mechanistic and predictive modeling of individual aging trajectories

Project

Understanding neurocognitive aging requires moving beyond group-average approaches toward individual-level modeling of variability. NEUROAGE proposes a precision neuropsychology framework integrating cognitive reserve and brain energy dynamics to explain resilience, vulnerability, and aging trajectories.

Framework

• Cognitive reserve formalized as a latent variable (CBR index)
• Brain energy quantified from functional connectivity
• Derived energy metrics: redistribution, cost, compensation
• AI-based phenotyping and trajectory prediction 

Approach

• Multimodal data (cognitive, behavioral, structural & functional connectivity, dynamics)
• Graph theory & structural balance
• Bayesian models, GAM, mediation analyses
• Machine learning 

Your role

• Structure and harmonize multimodal datasets
• Construct CBR index and energy metrics
• Model reserve–energy–cognition relationships
• Identify phenotypes and predict trajectories 

Profile

• PhD in computational neuroscience
• Strong neuroimaging expertise (fMRI, connectivity)
• Python, machine learning
• Experience with multivariate modeling (PCA/PLS) 

Plus: multimodal integration, dynamic modeling (HMM, MEG)

Environment

Laboratory of Psychology and Neurocognition (LPNC), CNRS UMR 5105 – Grenoble, France

Duration: 18 months (possible extension)

Application

CV, publications, selected papers, cover letter, 2 recommendation letters

📩 Contact: monica.baciuuniv-grenoble-alpes.fr (monica[dot]baciu[at]univ-grenoble-alpes[dot]fr)