A postdoctoral position in Machine Learning Edge Accelerators for Wearable Health Monitoring Devices is available in the Departments of Electrical and Communication Engineering, United Arab Emirates University, UAE. The postdoctoral candidate will develop an embedded system for recording vital signals (EEG, PPG, and ECG), predicting monitoring the patient’s health in real-time. The project goal is to develop wearable medical devices with on-device machine learning (ML) capabilities to offload some of the diagnosis and decision-making functions from the clinic to the edge device. The postdoctoral candidate will design, implement, and test innovative ML edge hardware accelerators within the stringent power, footprint, processing, and storage constraints of wearable health sensors. The developed ML edge accelerator will be optimized for different wearable health monitoring devices and applications. The sensor-centric health data will pave the way for the development of innovative healthcare solutions that can improve patient outcomes and reduce healthcare costs. A ML accelerator will be prototyped and tested for mental health monitoring. The postdoctoral candidate will help in advising MSc. and PhD. Students and participate in manuscript writing for publication in scientific journals and conferences.

• Applicants must hold a PhD or equivalent degree in electrical engineering, computer engineering, or computer sciences. • Applicants must have prior experience in machine learning, embedded systems, and edge devices. • Strong research in biomedical engineering using embedded systems and Machine learning. • Proven track record of publications in relevant IEEE journals and conferences.

• Candidates with a strong publication record in biomedical engineering will be given priority.

28/08/2024