Internship Opportunity at E3DA Research Unit - Real-time ERP Detection System for Research

FBK is opening a new internship opportunity in the Energy Efficient Embedded Digital Architectures - E3DA research unit of DigiS research center.
The Bruno Kessler Foundation is a research and innovation institution based in Trento. The Foundation operates in a plurality of disciplinary fields and aims to achieve excellence in science and technology through 2 science clusters, one dedicated to technology and innovation and one to humanities and social sciences, organized in 12 Research Centers, and with more than 450 researchers. For more information visit https://www.fbk.eu/it/chi-siamo/ .

In this context, the E3DA research unit focuses on wireless resource-constrained embedded technologies with a system-level approach targeting energy efficiency and Artificial Intelligence (AI) embedding at the very edge. The activity spans from hardware–software development for low-power wireless smart sensing devices to power management techniques, low-power multi-hop wireless protocols, and on-board processing in resource-limited devices, with a focus on Edge AI algorithms on multiple sensor data types (e.g., images, audio, biosignals, and others). Current research also includes Brain–Computer Interface (BCI) technologies, addressing efficient processing of brain signals for real-time applications (neurogaming, support systems).

Internship Opportunity
The student will develop and optimize a real-time Event-Related Potential (ERP) detection system for EEG biosignals using Python and PyTorch. They will then enhance system performance through iterative development and user study validation. The internship will be customized to suit the candidate's university major, research interests, and strengths.

Project Highlights
  • Develop a fully functional real-time system;
  • Deploy PyTorch/ONNX models in real-time inference mode;
  • Adapt the model to unseen users through fine-tuning and adaptation techniques;
  • Collect experimental data with integrated metrics and 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;
  • Experience with real-time systems and time-series analysis;
  • Good English proficiency for academic comprehension, work and participation in meetings with other International students and researchers.

Preferred
  • Experience with PyTorch/deep learning frameworks:
  • Understanding of biosignal processing techniques;
  • Knowledge of model deployment and optimization.

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