Cognitive Neuroscience and Psychophysiology: Multimodal Data Integration for the Study of Cognitive, Emotional, and Motor Processes

Profile:

The IMT School for Advanced Studies Lucca is seeking applications for 2 (two) research fellowships in the fields of cognitive neuroscience, psychology, and neuropsychology.
Candidates should preferably, though not necessarily, have a background in the acquisition and analysis of both central and peripheral physiological signals in humans. The ideal profile includes significant research experience in the simultaneous recording, pre-processing, and advanced analysis of multiple physiological signals – including those collected with portable devices – such as electroencephalography (EEG), peripheral body signals, psychometric measures, behavioral and kinematic data. Good programming skills and previous experience in developing analytical scripts for physiological and neuroimaging data are highly desirable. Prior research experience and/or scientific publications in the psychophysiological field will be considered an asset.
One fellowship will be primarily focused on the analysis of motor control and action representation, with a particular emphasis on resting-state fMRI data and correlations with behavioral/kinematic measures. The second fellowship will be dedicated to the analysis of behavioral and psychometric data in large samples, requiring strong computational and advanced data-analytical skills. Previous experience in either of these thematic or methodological areas will be considered a preferential requirement.

Activity:

Both fellows will be engaged in interdisciplinary research in cognitive and psychophysiological neuroscience, with a specific focus on the integration of multimodal data (neuroimaging, physiological signals, behavioral and psychometric measures) and on the development of advanced analytical methodologies to investigate the mechanisms underlying cognitive, emotional, and motor processes.
The first fellow will focus on research related to motor control and action representation. Specifically:
- Analysis of resting-state fMRI data, with the goal of identifying functional connectivity patterns within the motor system.
- Integration of neuroimaging data with behavioral and kinematic measures, to investigate the mechanisms of action planning and execution.
- Contribution to interdisciplinary projects aimed at linking resting-state brain dynamics with cognitive and motor functions.
The second fellow will be engaged in the analysis of behavioral and psychometric data in large samples. Specifically:
- Collection, organization, and management of large datasets including cognitive, emotional, and psychometric measures.
- Application of advanced computational and statistical methods (machine learning, predictive modeling, multivariate analysis) for data interpretation.
- Investigation of the relationships between psychometric profiles and cognitive/behavioral variables.
- Support in the development of digital tools and applications based on research findings.

Formal requirements:

• master’s degree (Laurea Magistrale) or equivalent qualification obtained abroad;
• good command of English (spoken and written).

Specific requirements:

The candidate must have a professional background to work in a highly collaborative and interdisciplinary team, even remotely.

Duration:

12 months

Gross amount:

€ 16.243,00 (for each position)

Project:

The scholarships referred to in this call for applications are funded with funds from the “Disagio giovanile Brescia: validazione di un intervento sperimentale per le scuole secondarie di primo grado” (Disagio giovanile Brescia) project, codice UGOV P0403, CUP D63C25000380007

Application:

Applications must be submit through PICA website only using the link at the bottom of this page.
Please note that for the submission of applications on PICA website, login via SPID IS NOT AVAILABLE at the moment - Please register using the alternative methods.

Si segnala che per la presentazione delle candidature sul sito PICA al momento NON E' DISPONIBILE il login tramite SPID - Si prega di effettuare la registrazione secondo le modalità alternative.