Privacy-preserving spiking neural networks for automatic speaker verification

PhD Position – Thesis offer M/F (Reference: SN/MT/PhD/SNN/012024)

EURECOM is looking for a highly motivated and talented PhD student to join our dynamic research team. Under the supervision of Prof. Massimiliano Todisco, this project represents a landmark in the field of technological innovation in speech technologies. The main objective is to address and solve two of the most urgent challenges in the field of speech and voice technologies: the critical need for increased privacy and the optimisation of energy efficiency. With the digital scene rapidly developing, protecting sensitive voice data from potential security vulnerabilities, and reducing the environmental impact of technology has never been more important.


  • Research development: the selected candidate will conduct fundamental research in the application of spiking neural networks for the processing of speech signals. This involves exploring both the theoretical underpinnings and practical implementations in the field.
  • Privacy focus: investigate innovative approaches to enhance the privacy of sensitive speech data during its processing, transmission, and storage, acknowledging the inherent risks in current voice-driven technologies.
  • Energy consumption optimisation: develop and test methods to reduce the energy consumption of always-listening devices, aligning with global efforts towards sustainable technology.
  • Real-world application: apply this research to speaker verification in realistic conditions, ensuring high standards of privacy and accuracy.
  • Collaborative efforts and dissemination: work within a multidisciplinary team and contribute to the broader academic community by publishing research findings, presenting at conferences, and participating in workshops and seminars.


  • A Master’s degree in Computer Science or a related field.
  • Strong background in machine learning and signal processing.
  • Good knowledge of cryptography and privacy enhancing technologies.
  • Familiarity with speech processing technologies.
  • Proficiency in Python and experience with deep learning frameworks, such as PyTorch.
  • Excellent analytical and problem-solving skills.
  • Strong communication skills in both written and spoken English.


The application must include:

  • a comprehensive CV
  • a letter of motivation detailing the suitability for the position
  • and the contact information for two references.

Applications should be submitted by e-mail to Prof Massimiliano TODISCO ( and CC with the reference:  SN/MT/PhD/SNN/012024

Start date: ASAP
Duration: Duration of the thesis


More info