{"id":77345,"date":"2021-07-28T03:00:06","date_gmt":"2021-07-28T01:00:06","guid":{"rendered":"https:\/\/www.cde.ual.es\/?p=77345"},"modified":"2021-09-06T13:53:42","modified_gmt":"2021-09-06T11:53:42","slug":"post-doctoral-fellowship-in-hardware-design-for-edge-machine-learning-processors-for-iot-sensors-in-ireland","status":"publish","type":"post","link":"https:\/\/www.cde.ual.es\/en\/post-doctoral-fellowship-in-hardware-design-for-edge-machine-learning-processors-for-iot-sensors-in-ireland\/","title":{"rendered":"Post-Doctoral Fellowship in Hardware Design for Edge Machine Learning Processors for IoT Sensors in Ireland"},"content":{"rendered":"

\"\"<\/a><\/p>\n

Offer description<\/h3>\n

This postdoc position is available at the Internet of Things Engineering lab at UCD Dublin in collaboration with MCCI. UCD researchers are currently developing low complexity deep neural network (DNN) techniques for deployment in IoT-enabled edge sensors for biomedical, industrial applications. Current efforts are focused on achieving optimization via model compression, quantization, etc. In this context, they are looking to hire multiple post-doctoral researchers who can conduct and supervise research on 1) development and optimization of DNN techniques for edge devices 2) Architectural design, circuit design, and implementation of efficient DNN accelerator hardware in terms of power, area, and performance. The candidate will also work in close collaboration with other hardware design researchers at UCD and MCCI tailoring DNN algorithms to support hardware limitations and opportunities. The selected candidates will have opportunities to co-supervise graduate students, participate in international conferences and collaborate with other academic and industrial researchers.<\/p>\n

Skills\/ Qualifications<\/h3>\n

Applicants for this position should ideally have:<\/u><\/p>\n