Multimodal NeuroAI and computational neuroscience for modelling brain dynamics

Italian Ministry of Education, University and Research; Italia; On-site; EUR 28,000 - 40,000; Full time

Job summary

Università degli studi di Roma Tor Vergata, Dipartimento di Biomedicina e Prevenzione, invites applications for a research fellow in BRAINFEDERATION to develop multimodal NeuroAI and computational neuroscience methods under the supervisor’s guidance.

Qualifications

• Eligibility of fellows: country/ies of residence: OTHER

Responsibilities

• Develop multimodal NeuroAI and computational neuroscience methods under supervision. Preprocess and integrate available neuroimaging data and electrophysiological signals, learn shared representations, and compare with dynamical models of neural populations and connectivity. Use experimental and simulated data with validation and robustness analyses.

Job description

Organisation/Company Università degli studi di Roma Tor Vergata Dipartimento di Biomedicina e Prevenzione Research Field Physics Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 19 Oct 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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Within BRAINFEDERATION, the appointee will support the development of multimodal NeuroAI and computational neuroscience methods to describe brain dynamics and responses to neuromodulation, under the scientific supervisor’s guidance. Activities will include preprocessing and integrating available neuroimaging data and electrophysiological signals, learning shared representations, and comparison with dynamical models of neural populations and connectivity. Experimental and simulated data will be used, with validation on subjects or sessions held out from training, uncertainty analysis and assessment of robustness to missing modalities. Outputs will include documented code, reproducible procedures and a report on the results, supporting neural-state estimation and closed-loop control

• Italy

Eligibility of fellows: country/ies of residence:

• OTHER