Job Description
The researcher will be assigned to develop the machine-learning enabled synthesis method and algorithms to enhance performance of phased array antennas.
The researcher will study the fundamentals of phased array theory and the model of phased array using neural network-based algorithms.
The scanning range of a large-scale phased array will be enhanced over a wide bandwidth with high gain.
The results will lead to papers to be published at prestigious journals.
Qualifications
- PhD holders in the fields of electromagnetic and antenna engineering
- At least 2-year experience in programming machine learning/neural network algorithms
- Experience in design of phased arrays
- Good record in paper publications in prestigious journals such as IEEE Trans AP
- Good communication skills and writing papers in English
- Open to Fixed Term Contract
More Information
Location: Kent Ridge Campus
Organization: College of Design and Engineering
Department: Electrical and Computer Engineering
Employee Referral Eligible: No
Job requisition ID: 22977
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