Open PhD Position in Brain Connectivity and Artificial Intelligence
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Paolo Avesani
May 23, 2025, 1:21:38 PM5/23/25
to ml-...@googlegroups.com, Ludovico Coletta
OPEN PHD POSITION IN BRAIN CONNECTIVITY AND ARTIFICIAL INTELLIGENCE
4 years PhD Scholarship in the Doctoral Programme in Cognitive and Brain Sciences, University of Trento.
A PhD position funded by Neuroinformatics Laboratory, Fondazione Bruno Kessler, Trento, Italy.
Contact: Ludovico Coletta (lcol...@fbk.eu)
Important dates:
Deadline for application: 5 June 2025
Beginning of PhD program: 1 November 2025
Deadline for application: 5 June 2025
Beginning of PhD program: 1 November 2025
Apply now:
(PhD Programme in Cognitive and Brain Sciences 41st cycle - Topic specific grant: AI and Neuroscience)
Research Topic
The economic impact of psychiatric disorders is projected to surpass that of cancer, diabetes, and respiratory diseases combined, highlighting a significant health crisis that demands urgent action. The advent of Magnetic Resonance Imaging (MRI) and functional MRI (fMRI) enabled the non-invasive measurement of structural and functional principles of brain organization across both health and disease, without achieving clinical translation. The hypothesis at the core of the PhD project is that the universally adopted pre-processing strategies and analytical approaches are hampering the development of such translational tools.
The primary aim of the project [AIM 1] is to develop an artificial intelligence-based solution that bypasses canonical preprocessing strategies and analytical approaches. If successful, the PhD applicant will provide a radical new solution to model inter-individual variability, overcoming the major pitfalls of the state-of-the art.
Akin to the revolution sparked by the introduction of general-purpose artificial intelligence models – also known as foundation models – the project aims to develop a similar framework to model interindividual variability in brain connectivity. The proposed architecture will capture structural, morphological and functional aspects of the brain’s intrinsic organization, analogously to the ability of foundation models to process audio, text, and images.
In keeping with the possibility of foundation models to be easily adapted to the users’ needs, the secondary aim [AIM 2] of the project is to investigate model fine tuning in psychiatric settings. The research questions are devoted to probe the overall clinical validity, the investigation of ethnic and gender biases, and the feasibility of predicting the long-term trajectory of mental health conditions.
The successful candidate will have a MSc in computer science, biomedical engineering, physics, or any STEM discipline. Hands-on training in neuroimaging data analysis and geometric deep learning and/or software tools for brain connectivity will be highly valued.
The primary aim of the project [AIM 1] is to develop an artificial intelligence-based solution that bypasses canonical preprocessing strategies and analytical approaches. If successful, the PhD applicant will provide a radical new solution to model inter-individual variability, overcoming the major pitfalls of the state-of-the art.
Akin to the revolution sparked by the introduction of general-purpose artificial intelligence models – also known as foundation models – the project aims to develop a similar framework to model interindividual variability in brain connectivity. The proposed architecture will capture structural, morphological and functional aspects of the brain’s intrinsic organization, analogously to the ability of foundation models to process audio, text, and images.
In keeping with the possibility of foundation models to be easily adapted to the users’ needs, the secondary aim [AIM 2] of the project is to investigate model fine tuning in psychiatric settings. The research questions are devoted to probe the overall clinical validity, the investigation of ethnic and gender biases, and the feasibility of predicting the long-term trajectory of mental health conditions.
The successful candidate will have a MSc in computer science, biomedical engineering, physics, or any STEM discipline. Hands-on training in neuroimaging data analysis and geometric deep learning and/or software tools for brain connectivity will be highly valued.
The University of Trento ranks among top Italian Universities (https://www.unitn.it/en/ateneo/1636/rankings).
Fondazione Bruno Kessler ranks first among the Italian research centers in Engineering and Computer Science
(https://magazine.fbk.eu/en/news/fbk-ranks-1st-in-italy-for-scientific-excellence-in-three-areas).
Why choose Trento?
(http://www.unitn.it/en/ateneo/1629/why-choose-the-university-of-trento)
(https://magazine.fbk.eu/en/news/fbk-ranks-1st-in-italy-for-scientific-excellence-in-three-areas).
Why choose Trento?
(http://www.unitn.it/en/ateneo/1629/why-choose-the-university-of-trento)
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