Job Description

A research assistant is required to work at the College of Information Technology, United Arab Emirates University. We seek a highly motivated and skilled research assistant to contribute to the development of a Smart Respiratory Health Monitoring System using RF-based sensing and machine learning. The candidate will participate in the design, simulation, development, and field testing of a non-contact, real-time respiratory monitoring system tailored for industrial environments. The duties include: o Developing and optimizing RF-based sensing algorithms for respiratory monitoring using Software-Defined Radio (SDR) platforms. o Implementing adaptive machine learning models (e.g., LSTM, lightweight CNNs) for anomaly detection in respiratory patterns. o Integrating cloud-based platforms for data management and visualization dashboards. o Conducting field validation in dynamic outdoor industrial settings with multiple-person monitoring. o Supporting the preparation of research deliverables, including technical reports, publications, and progress updates. Essential Requirements: o Strong experience in wireless communication, RF sensing, and signal processing. o Hands-on experience with network simulators (such as NS-3) or software-defined radio (such as USRP, HackRF). o Solid background in machine learning algorithms and real-time data analysis (preferably for health monitoring or sensor data). o Good programming skills (e.g., Python, MATLAB, or C++). o Strong oral and written communication skills in English. o Ability to work independently and collaboratively in a multidisciplinary research team. Preferred Experience: o Prior work on health monitoring, non-invasive sensing technologies, or respiratory signal analysis. o Experience with cloud computing platforms and developing dashboards for health data visualization. o Knowledge of federated learning or transfer learning techniques is a plus.



Minimum Qualification



Master's degree in Computer Engineering, Computer Science, Electrical Engineering, Communications, or a related field.



Preferred Qualification



Master's or Ph.D. in Computer Engineering, Electrical Engineering, Networking, Machine Learning, or related areas.



Expected Skills



Experience with RF signal processing, machine learning integration, wireless networking, and system prototyping.



Special Instructions to Applicant



Please attach a detailed CV and a cover letter highlighting relevant experience



Salary Range



Commensurate with qualifications and experience.



Close Date Kindly apply before the closing date.



31/08/2025