
Internship Opportunity at E3DA Research Unit - Adaptive neural architectures for BCI
- Trento
- Formazione
- Full time
The student will develop a low consumption architecture for real-time detection of BCI commands. The main goal is to generalize across subjects, tasks and time, thus adapting the model to inter-individual and inter-session differences.The architecture will be deployed and evaluated offline on a microcontroller unit (MCU) or IOT device (Raspberry, Jetson). The internship will be customized to suit the candidate's university major, research interests, and strengths.Project Highlights
Develop a generalized architecture with state-of-the-art techniques for detecting multiple BCI commands and adjusting to individual differences;
Develop an explainability layer (XAI) to investigate the neuroscientific soundness of the model;
Deploy the model natively in resource-constrained environments (MCU, Raspberry, Jetson);
Optimize resource usage and energy consumption through experimental evaluation.
Required background
Academic background in Engineering, Physics, Mathematics, or related technical field;
Proficiency in object-oriented programming and Python;
Knowledge of neural networks and deep learning fundamentals;
Proficiency with at least one deep learning framework (PyTorch, Tensorflow, Keras);
Good English proficiency for academic comprehension, work and participation in meetings with other International students and researche.
Preferred
Experience with design of experimental tasks evaluation;
Understanding of biosignal processing techniques;
Knowledge of model optimization (quantization, pruning) and hyperparameters optimization;
Knowledge of embedded systems and MCU programming.
Additional Opportunity
This internship may be extended into a full research thesis for interested candidates.We offer
Curricular internship;
3-6 months, the opportunity can be extended for thesis upon request;
Canteen;
Support for the search for accommodation at the affiliated structures. All interested parties are requested to fill in the online form, clicking on "Apply online", and attach the required documents in Pdfs format:
Curriculum Vitae;
Cover letter;
Reference letter (optional). Applications will be reviewed as they arrive. Preferred period: Fall 2025 to winter 2026.
For any information, contact Michele Romani (miromani@fbk.eu).For any support, further clarification and/or information, the Human Resources Department will remain
available via the address: jobs@fbk.eu