PhD Position on "Secure Machine Learning on RISC-V Servers and Accelerators" - Zürich, Schweiz - Digital Circuits and Systems Group

    Digital Circuits and Systems Group
    Digital Circuits and Systems Group Zürich, Schweiz

    vor 2 Wochen

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    fixed-term
    Beschreibung

    Job description

  • You will be developing a platform for the secure deployment of Machine Learning inference tasks on multi-tenant machines. An example of security-critical application is running a foundation model for biosignal analysis (e.g., EEG signals) for different users, ensuring confidentiality for each user
  • You will be optimizing secure ML task execution for RISC-V hardware platforms, addressing these open research challenges: Energy Efficiency Optimization: Enhancing the energy efficiency of ML algorithms to ensure they can operate within the stringent power budgets of devices ranging from low-power IoT sensors to high-power data centers Performance Scaling: Scaling the performance of ML tasks across a wide operating range, ensuring optimal utilization of available computing resources in both low-power (limited number of cores) and high-performance scenarios (many cores platforms) Hardware Acceleration: Leveraging hardware accelerators to improve the speed and efficiency of ML tasks, including custom RISC-V extensions and co-processor design, or drivers for already designed accelerators Encryption and decryption of user data and user-specific privacy-preserving fine-tuning of models Algorithm-Hardware Co-Design: Working closely with circuit and system designers to influence the architectural decisions of future RISC-V platforms, ensuring that the hardware is optimized for advanced ML applications
  • You will be collaborating with colleagues from the high-level Machine Learning domain and digital-design domain
  • You will be responsible for project meetings, reporting, scientific publications, and conference/seminar presentations
  • You will supervise master/bachelor students
  • You will be involved in teaching activities

    • Your profile

  • MS in Electrical Engineering, Computer Science, or related field with a good background in computer architecture
  • Proven skills in software profiling and optimization for target platforms with familiarity with Machine Learning workloads
  • Exposure to the design and deployment of Machine Learning inference tasks on servers and hardware accelerators
  • Understanding of the basic concepts of computer security
  • Some familiarity with RISC-V –based platforms
  • We are looking for good team players, with excellent English written and verbal communication skills.
  • Research and publication track record in RISC-V-based digital design is a plus
  • Research and publication track record in Machine Learning for embedded systems is a plus