HiPEAC invites applications for a full-time doctoral position in Madrid working on scalable, low-precision Graph Neural Networks for edge inference and training.
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The project spans heterogeneous hardware/software co-design using Versal AI Engine and FPGA accelerators, with a focus on energy efficiency and sub-millisecond latency.
The candidate will develop quantisation techniques, C/C++/Python xqbhyrx implementations, and collaborate with an international team on European projects, with health insurance
📌 Edge GNNs: Low-Precision, Heterogeneous Hardware (Madrid)
🏢 HiPEAC
📍 Madrid