Research Fellow / Engineer, Software Defined Radio
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- 17 Feb 2023
- End of advertisement period
- 30 Apr 2023
- Academic Discipline
- Engineering & Technology, Computer Science, Electrical & Electronic Engineering
- Contract Type
- Fixed Term
- Full Time
As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT.
As part of the 5G Trans Lab@SIT, the primary responsibility of this role is to design and implement the hardware and software architecture for software defined radios (SDR) to support open radio access network (O-RAN), validate novel features and interface specifications, support new use case and application development, conduct performance testing of the design in the 5G testbed, to realize the required quality of service performance. You will also be working with the team mates to support innovation projects in collaboration with industry partners.
As a SDR Research Fellow/Engineer, you will need to closely coordinate and work with the PI. Major responsibilities include,
- Hardware and software architecture for software defined radios (SDR).
- Designing, simulation, implementing and testing of new SDR architecture and solutions in real 5G networked testbed.
- Practical hands-on experience with physical wireless network including front-end and back-end interfaces and constraints.
- Knowledge of hardware and software tools for application of SDR in real 5G network.
- Cognitive radio using machine learning and other advance techniques (e.g. deep learning, neural network)
- A relevant PhD/Master’s degree in communication/wireless networks.
- Working knowledge in 5G systems.
- Have hands-on competence in the areas of data analytics, deep learning and artificial intelligence.
- Ability to work independently.
- Knowledge of wireless communication and mobile cellular networks.
- Experience working with time series data and Python/C++/MATLAB.