PHD STUDENT (Ref. 2025-009-P04632)

Somma; Barcelona; Presencial; EUR 22.000 - 30.000; Jornada completa

Descripción de la vacante

The CRM in Barcelona is looking for a PhD student to work on an innovative project in Computational Neuroscience focused on predicting Alzheimer's disease progression. This will involve developing reliable models using extensive datasets over the next four years, aiming for critical advancements in personalized treatment strategies.

Formación

• Experience in statistical modeling and data analysis.
• Strong interest in computational neuroscience and Alzheimer’s disease.
• Familiarity with working on large datasets.

Responsabilidades

• Develop predictive models for Alzheimer's disease progression.
• Analyze neuroimaging and clinical data.
• Collaborate with the Vidaurre group at CRM.

Conocimientos

Statistical modeling

Computational neuroscience

Data analysis

Educación

Master's degree in neuroscience, mathematics, or related field

Descripción del empleo

Job Opportunity : PhD Student in Computational Neuroscience at CRM

The CRM ( is an independent research centre within the CERCA network since 2008, dedicated to promoting advanced training and research in all areas of mathematics, in collaboration with universities and research institutions across Catalonia. CRM’s mission includes transferring research knowledge to society and aiming for societal impact.

Research at CRM spans fundamental fields such as algebra, number theory, geometry, topology, analysis, PDEs, combinatorics, and dynamical systems, as well as applied mathematics in biomedicine, climate change, and natural hazards.

The Computational Neuroscience — Vidaurre group at CRM is seeking a PhD student to join the project titled “A new integrative statistical framework to connect symptoms to mechanisms in brain disease” (project code : Actuación ATR2024-155014 , funded by MICIU / AEI).

This contract is expected to commence on September 1, 2025, and will last until August 30, 2029.

Project Overview

The project focuses on predicting disease progression (prognosis) in Alzheimer’s disease, which is crucial for personalized treatment and future care planning. Current prognostic models are limited, and this project aims to develop detailed, reliable models using a large longitudinal dataset from a dementia clinic in Barcelona.

The dataset includes clinical features, neuropsychological tests, MRI and PET imaging, CSF biomarkers, and genetics from over 20,000 patients evaluated over the past 10 years. The project will leverage public datasets like ADNI to learn meaningful neuroimaging features, which will be integrated with clinical data to predict disease trajectories.

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