- Support architecture studies, performance analysis, and design studies
- Participate in research activities focused on edge compute architecture
- Currently has, or is in the process of obtaining a PhD in the fields of Electrical Engineering, Computer Engineering, Computer Science, or related field
- 2+ years research experience in one or more of the following: Machine learning accelerator / inference engine for deep neural networks (DNN), Algorithms to perform low precision arithmetic for deep learning, Quantization and sparsity techniques for efficient, low-precision inference, Computer architecture for mobile and/or embedded systems, Deployment of computer vision methods on embedded systems, Hardware design with Magma, Chisel, Google XLS, or any high level synthesis (HLS) languages
- 2+ years of experience programming with Python
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
- Experience developing or optimizing CV and ML algorithms for vision tasks
- Experience with Tensorflow, Tensorflow Lite, and Pytorch software stacks
- Experience in system modeling for all aspects of a digital system
- Experience with synchronous and asynchronous communication protocols (e.g. I3C, CSI-2, SPI, UCIe, PCIe)
- Proven track record of achieving significant results as demonstrated by grants, or fellowships, as well as first-authored publications in major conferences and journals such as ICCAD, DAC, ISCA, MICRO, HPCA, ISSCC, TinyML, IEDM, VLSI Symposium, ASPLOS, JSSC, TCAS
- Intent to return to degree-program after the completion of the internship
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