Computational Modeling and Multimodal Integration of EEG and Functional Ultrasound Imaging

Italian Ministry of Education, University and Research; Italia; On-site; EUR 28,000 - 48,000; Part time

Job summary

Sapienza Università di Roma invites applications for a research position to develop and validate multiscale computational models of brain activity, integrating EEG and fUS data. The work includes neuronal dynamics simulation, neurovascular coupling models, and EEG source-space analysis, with exposure to machine learning methods such as reservoir computing and deep learning to classify brain states.

Experiments will utilize simultaneous EEG–fUS data; country: Italy.

Qualifications

• Development and validation of multiscale computational models of brain activity.

Responsibilities

• Develop and validate multiscale computational models of brain activity.

Skills

Neuronal dynamics simulation

EEG–fUS data analysis

Neurovascular coupling models

Spiking neural networks

Machine learning methods

Reservoir computing

Deep learning

Tools

EEG

fUS

Job description

Organisation/Company SAPIENZA UNIVERSITA' DI ROMA Research Field Engineering » Biomedical engineering Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 20 Nov 2026 - 23:59 (UTC) Country Italy Type of Contract To be defined Job Status Not Applicable Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Development and validation of multiscale computational models of brain activity for the integration and interpretation of electroencephalographic (EEG) signals and functional ultrasound (fUS) imaging data.
Specific activities will include the simulation of neuronal dynamics and the associated electrophysiological and hemodynamic signals, also by means of spiking neural networks and neurovascular coupling models; EEG source-space analysis; and the development of machine learning methods, including reservoir computing and deep learning, to identify and classify physiological and pathological brain states.
The developed methods will be tested on experimental data obtained from simultaneous EEG–fUS recordings.

• Italy

Eligibility of fellows: country/ies of residence:

• OTHER
• E.U.