Assistant Professor School of Microelectronics
Dr. Yida Li is currently an Assistant Professor at the Southern University of Science and Technology, Shenzhen, China. He graduated from the National University of Singapore with a Ph.D. degree in Integrative Science and Engineering Program in 2013. From 2014 to 2016, he was with Taiwan Semiconductor Manufacturing Company (TSMC), Hsinchu as a process R&D principal engineer working on metal deposition and sillicidation at the 7/5 nm technology node, with both technology node currently in mass production. From 2016 to 2020, he was a research fellow at the National University of Singapore working with Professor Aaron Thean.
Dr. Li has published more than 40 papers in international academic journals and conferences. His work presented in VLSI 2018, Honolulu, USA was featured in prominent industry magazine, Compound Semiconductor. In addition, he has given invited talks at renowned international conferences including Graphene Flagship 2019 and VLSID 2020.
1. Novel/Emerging memory and logic devices targeting at Non-Von Neumann computing architecture and neuromorphic circuits
2. Hardware accelerators and compute-in-memory system architecture
SME102 (Spring) - Microelectronics Fundamentals (Undergraduate)
To introduce the basic concepts, basic laws, theorems and analysis methods of electric circuits and the basic physics of semiconductor devices. Applications of devices in building amplifier, logic gates, basic circuits and CMOS Process will also be taught.
SME203 (Autumn) - Fundamentals of Microelectronics I (Undergraduate)
The course will introduce students to the materials physics behind semiconductor devices, including their applications and processing. Topics for the course include kinetic molecular theory and thermally activated processes; electrical and thermal conductivity of metals and semiconductors; introductory quantum mechanics for materials science; band structure and intrinsic and extrinsic semiconductors.
SME204 (Spring) - Fundamental of Microelectronics II (Undergraduate)
The course will introduce students to the underlying physics and mechanisms in legacy semiconductor devices including PN Diode, Bipolar Junction Transistor, Metal-Oxide-Semiconductor Field-Effect Transistor. Device simulation using TCAD software will also be introduced.
SME5024 (Spring) - Introduction to In-Memory Computing - From Materials to System (Graduate)
This course will introduce graduate students to one of the most popular non-von Neumann computing architecture that is slated to be implemented in future computer chips for abundant data calculation. Concepts to be taught to students will include 1. Non- von neumann computing architecture, 2. Emerging devices for in-memory computing, 3. Analog Memory Programming Techniques and Variations, 4. Artificial Neural Networks based on In-memory computing, 5. Circuit Primitives for Analog Computing.
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Research topics include but not limited to:
Novel/Emerging memory and logic devices targeting at Non-Von Neumann computing architecture and neuromorphic circuits
Hardware accelerators and compute-in-memory system architecture
Required/Desired Skills and Qualifications:
Degree in Electrical & Electronic/Material Science/Biology and Chemical Engineering or other related fields
Motivated and cheerful individual, able to work under stress
Independent research thinking ability and to identify and solve problem systematically
Responsible individual with great team spirit
Good English listening, speaking, reading and writing skills,
Experience in at least 1 of the following
nano-fabrication, nano-materials, memory and logic devices characterization, modelling
2 related publications as first/corr-authors
The postdoctoral position has an age limit of 35 year old
A contract period of 2 years
Successful candidate will enjoy an initial annual salary exceeding 350,000 RMB (depending on qualifications)
Multiple research grants provided by Shenzhen government
How to apply:
Interested individuals are invited to email a copy of his/her CV to the below email address, with subject titled “Research position application <Position, Name>”.
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