Devices, Circuits and Architectures for Neuromorphic Computing
NIST is researching new computer architectures & circuits for AI using exotic devices and CMOS, exploring device fabrication, circuit design, & algorithms.
This grant is no longer accepting proposals
NRC Research Associateship Programs has archived this opportunity.
Funder: NRC Research Associateship Programs
Due Dates: February 1, 2025 | May 1, 2025 | August 1, 2025 | November 1, 2025
Funding Amounts: Stipend approximately $82,764/year plus $3,000 travel allowance; typical appointment duration 2 years.
Summary: Postdoctoral fellowship at NIST to develop devices, circuits, and architectures for neuromorphic computing using exotic devices combined with CMOS circuits, focusing on hardware-based AI systems and metrology.
Key Information: Open to U.S. citizens with a Ph.D.; requires contacting a Research Adviser prior to applying; NIST participates in February and August review cycles.
Description
The National Institute of Standards and Technology (NIST) offers a postdoctoral research opportunity through the NRC Research Associateship Programs focused on advancing neuromorphic computing. The Alternative Computing Group at NIST is developing prototype circuits and novel architectures that integrate exotic devices—such as metal-oxide and phase-change memristors, magnetic tunnel junctions, and Josephson junctions—with custom-designed CMOS circuits. These efforts aim to realize functionalities including crossbar-based machine learning and race-logic-based DNA sequencing.
Research opportunities include:
- Experimental device fabrication and measurement using NIST’s state-of-the-art NanoFab and measurement facilities.
- CMOS circuit design for foundry tape-out.
- Theoretical development of algorithms and architectures that leverage the unique properties of emerging devices, such as low energy consumption and high speed.
The ultimate goal is to explore hardware-based artificial intelligence systems and to understand the critical role of measurement and metrology in these complex, adaptive systems.
Key research areas include neuromorphic computing, artificial intelligence, memristors, resistive RAM (RRAM), CMOS circuit design, machine learning, cognitive computing, phase change memory, superconducting circuits, magnetic tunnel junctions, and race logic.
