Phd Candidate for Deep Reinforcement Learning for Energy-Efficient Resource Allocation Optimization

Description
Energy efficiency (EE) has become an important criterion for designing the next generation (5G) communication systems. Conventional energy-efficient resource allocation algorithms generally consider the overall EE problem as nonlinear fractional program. This project aims to address the complicated problems with the aid of deep reinforcement learning.

Location
UTAR Sungai Long Campus, Malaysia

Monthly stipend
Up to RM 3,300 (Depending on Qualifications and Experience)

Pre-requisite Degree
MEng/MSc and BEng/BSc (CGPA>3.0) in a field related to Electrical, Electronic, Telecommunications Engineering, IT or Computer Science.

General Requirements
• Excellent command of English
• Able to work with minimal supervision, self-motivated and independent
• Good track records in journal publications (an added advantage)

Expected Outcomes
Publications in ISI Journals and Top Conference Proceedings

How to Apply?
Interested candidates may submit their resumes to Assist. Prof. Dr. Tham Mau Luen at thamml@utar.edu.my.
Only shortlisted applicants will be notified and called for interview.

Deadline
Until the position is taken (from August 2018)