Master in Neural Engineering

This Master’s program trains highly skilled professionals in neural engineering by integrating neuroscience, advanced technologies, and artificial intelligence. Students acquire state-of-the-art expertise in brain monitoring, modeling, and brain-machine interaction, with strong foundations in neuroimaging, neural signal analysis, computational neuroscience, and neural interfaces.

Graduates are prepared for careers in research institutions, high-tech and medical device industries, neurotechnology startups, and clinical settings, as well as for participation in international research projects or further training through PhD programs at the forefront of next-generation neurotechnologies.

The Future of Neuroengineering Starts Here!

Call (in Italian): Master Universitario di I livello annuale in Ingegneria Neurale/Neural Engineering | Università degli Studi "G. d'Annunzio" Chieti – Pescara

Contact: laura.marzetti@unich.it

Training Plan 2025/2026

Technologies and Principles of Neuroimaging                                 

  • Principles of MRI, DW-MRI and fMRI – F. Dell' Acqua, King’s College London
  • Principles of EEG and MEG – V. Pizzella, Univ. of Chieti-Pescara
  • Novel imaging technologies – J. Haueisen, TU Ilmenau
  • Functional Neuroanatomy – M. Catani & M. Bisconti, Univ. of Chieti-Pescara

Data Analysis and Computational Modeling in Neuroimaging

  • Signal processing for structural and functional MRI – R. Guidotti, Univ. of Chieti-Pescara
  • EEG/MEG data analysis: forward and inverse problem, brain oscillations and connectivity – L. Marzetti, Univ. of Chieti-Pescara & O. Hauk, Univ. of Cambridge
  • Brain networks and graph analysis Basti, Univ. of Chieti-Pescara

System neuroengineering                                                                          

  • Control Theory – F. Camilli, Univ. of Chieti-Pescara
  • Wearable and Implantable Sensors – D. Cardone, Univ. of Chieti-Pescara
  • Neurostimulation technologies – V.H. Souza, Aalto University & A. Fraleoni Morgera, Univ. of Chieti-Pescara
  • EEG-TMS integration and brain-state dependent stimulation - S. Casarotto, Univ. of Milan
  • Neurofeedback and Intelligent Closed-Loop Systems – D. Yao, UESTC
  • Human-artificial agent interaction and affective computing – A. Merla, Univ. of Chieti-Pescara

Artificial Intelligence and Computational Neuroscience

  • Brain modeling across scales – G. Rabuffo, Aix-Marseille Univ.
  • Soft tissue biomechanics of the brain – C. Falcinelli & M. Vasta, Univ. of Chieti-Pescara
  • Probability Theory for AI – S. Doria, Univ. of Chieti-Pescara
  • Fundaments of machine learning Caroprese, Univ. of Chieti-Pescara
  • Machine Learning and AI-driven diagnostics – M.C. Corsi, Paris Brain Institute & M. De Muru, Univ. of Naples
  • Neuroinformatics & Big Data – G. Niso, Cajal Institute Madrid

Clinical, Translational and Entrepreneurship Applications       

  • Clinical translation of neural engineering tools – P. Sorrentino, Aix-Marseille Univ.
  • Trends in Neural Regenerative Medicine – E. Battista, Univ. of Chieti-Pescara
  • Scientific Writing and Neuroscientific Research – A. Luppi, Univ. of Oxford
  • Innovation, Patents, and Startup Entrepreneurship – A. Merla, Univ. of Chieti-Pescara

Scopri cosa vuol dire essere dell'Ud'A

SEDE DI CHIETI
Via dei Vestini,31
Centralino 0871.3551

SEDE DI PESCARA
Viale Pindaro,42
Centralino 085.45371

email: info@unich.it
PEC: ateneo@pec.unich.it
Partita IVA 01335970693

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