(one year contract)
- Closing on March 02, 2022
Singapore Management University is a place where high-level professionalism blends with healthy informality. The “family” atmosphere within the SMU community fosters a culture where employees work, plan, organize, and play together, which builds collegiality and morale within the university.
Our commitment to attracting and retaining talent continues. We offer attractive benefits, competitive compensation and generous professional development opportunities, all to meet the professional and personal needs of our staff. It’s no wonder, then, that SMU continues to receive numerous awards and recognitions for the excellence of its human resources.
- Develop and implement new forms of sensing protocols and energy efficient hardware prototypes, supporting new forms of energy harvesting and RF power transfer
- Implement new system-level algorithms and optimizations for low-power multimodal sensing that leverages wearable and infrastructure (loT) sensors, with a particular focus on audio/voice detection and sensing technologies neuromorphic
- Conduct experimental studies to quantify the performance of the resulting system and generate appropriate analytical artifacts (e.g. graphs, reports) to document that performance
- Support the research team to produce high quality research publications
- Minimum bachelor’s degree in computer science, information technology, information systems or closely related disciplines
- 1+ year of relevant research experience in energy harvesting technologies and development of low power consumption IoT/wearable systems
- Coding experience with programmable embedded and experimental platforms, such as ARM, RaspberryPI, ATMEGA, etc. is essential.
- Project-level experience with low-power system optimization and firmware-level programming, particularly for visual or audio detection and signal processing algorithms (e.g., frequency domain filtering ) is strongly desired.
- Proven experience in embedded systems design (e.g. with FPGAs) and applications for embedded sensing and microprocessor platforms
- The ability to work cooperatively within a small, agile academic research team is essential.
- University level knowledge of signal processing and wireless sensor networks is desirable
- Experience in conducting careful systems-level studies of sensor hardware, using tools such as Monsoon Power Monitor, is highly preferred
- High-quality publications in academic venues related to pervasive and ubiquitous computing are desirable