Research Fellow, 2D Flexible Electronics
The Research Fellow will work on the preparation and characterization of high-quality two-dimensional materials and heterostructures, as well as their potential applications in electronics and flexible electronics. The candidate will also develop the new selective sensing strategy via the biomimetic structure design, which will be used in interactive entertainment and other promising human-machine interactions. The project combines the fields in materials science, device physics and machine learning assisted system integration with the aims of 1) fabricate and characterize the 2D materials based biomimetic sensor; 2) investigate the 2D materials-based sensing strategy via finite element analysis of interface mechanics and heat transfer, and explain how the nanomaterial and microstructures to contribute to the selective properties; 3) utilize different machine learning methods to distil information from complex sensor data and 4) integrate the sensor, read out circuit and machine learning module into a multifunctional biomimetic system.
- The candidate will be enrolled in the 2D materials group, mainly working on the electrical properties of 2D materials-based electronic devices
- The candidate should have good personality, able to work closely with collaborators in nanomaterials, transport, STEM and computing
- The candidate will fabricate 2D materials and carbon-based nanomaterials
- The candidate should have excellent presentation skills, with rich experience in oral and poster presentations in international conferences or meetings
- The candidate should have software skills, like Adobe Illustrator, Adobe Photoshop, 3ds max, blender, MATLAB, etc
- Good communication skills in English (both written and oral) are required
- PhD graduated in physics, condensed matter physics and materials
- More than 4 years research experience in related areas, including the preparation of van der Waals materials, high-quality monolayer transition metal dichalcogenides and graphene, flexible electronics and machine learning
- Familiar with cryogenic measurement, e-beam lithography, plasma etching, scanning electron microscopy, scanning tunneling spectroscopy, wire bonding, the wet/dry transfer technique, etc
At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presence is required.
Taking into consideration the health and well-being of our staff and students and to better protect everyone in the campus, applicants are strongly encouraged to have themselves fully COVID-19 vaccinated to secure successful employment with NUS.
Location: Kent Ridge Campus
Organization: Institute for Functional Intelligent Materials
Department : Research Groups
Employee Referral Eligible: No
Job requisition ID : 16963