This PhD studentship aims at using and developing the stochastic computing principles in collaboration with the emerging technology devices (like ReRAM, STT, .. etc) to sustain the increasing performance demands of the data-intensive AI applications. While merging the high capacity and non-volatility of the emerging devices with the emerging in-memory computing architectures can hopefully mitigate the memory bottleneck of the Von Neumann architectures, the stochastic computing is proposed to extremely reduce the computation complexity/cost of the conventional binary system. The different challenges of the stochastic computing will be addressed through the potential promise of both emerging devices and architectures.
We welcome applications from candidates with a background in electronics, IC design and computer architecture. Specific areas of interest include: energy efficient IC design, stochastic computing, in-memory computing and AI applications. Interested candidates are encouraged to contact Dr Shady Agwa (email@example.com).