Erasmus+ Neuroscience Imaging Intern

12 ago - Trento
Aretè & Cocchi Technology

ERASMUS+ INTERNSHIP in LIFE TECHNOLOGIES / Identify relevant networks in the mouse brain through correlation of fMRI and behavioral scores
Commitment & contract: Full-time internship within the Erasmus+ Traineeship programme for undergraduate students enrolled in a master’s degree programme; the position requires a time commitment of 40 hours/week (tempo pieno)
Location: Center for Neuroscience and Cognitive Systems, Rovereto (Trento), Italy
Duration: 6 months
Start date: 15/09/2026 (flexible)
Compensation: No salary granted by IIT (applicants must rely on funding from their University’s Erasmus+ programme)
Step into a world of endless possibilities, together let’s leave something for the future
At IIT, we are committed to advancing human-centered Science and Technology to address the most urgent societal challenges of our era. We foster excellence in both fundamental and applied research, spanning fields such as neuroscience and cognition, humanoid technologies and robotics, artificial intelligence, nanotechnology, and material sciences,



offering a truly interdisciplinary scientific experience. Our approach integrates cutting-edge tools and technology, empowering researchers to push the limits of knowledge and innovation. With us, your curiosity will know no bounds.
We are dedicated to providing equal employment opportunities and fostering diversity in all its forms, creating an inclusive environment. We value the unique experiences, knowledge, backgrounds, cultures, and perspectives of our people. By embracing diversity, we believe science can achieve its fullest potential.
THE ROLE
During your internship you will work on a project in the Functional neuroimaging group (https://fnimg.iit.it/it/) coordinated by Alessandro Gozz. This group focuses on System and computational neuroscience.
Your activity will comprise
- fMRI image pre-processing
- fMRI image analysis

And will allow you to develop competences in
- Analysis of complex neuroimaging datasets

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