Job Title Postdoctoral Fellowship in Memristor-Based Neuromorphic Computing, In-Memory Computing, and CIM-Based AI Accelerators

- Conduct research on memristor device modeling, characterization, and performance optimization for computing applications.

- Develop neuromorphic architectures inspired by biological neural systems for effective signal and pattern processing.

- Design and implement in-memory computing circuits and computing-in-memory (CIM) based AI accelerators.

- Perform simulations using industry-standard EDA tools, device simulators, and circuit-level modeling software.

- Prototype and evaluate hardware implementations on FPGA/ASIC platforms or crossbar arrays.

- Collaborate with multidisciplinary teams working in nanofabrication, electronics, and machine learning.

- Publish high-quality research outcomes in top-tier journals and conferences.

- Contribute to project documentation, grant activities

Research Areas





- Memristor device modeling and performance optimization for computing applications.

- Neuromorphic circuit and architecture design inspired by biological neural systems.

- In-memory computing techniques using memristor crossbar arrays for AI workloads.

- Energy-efficient CIM-based AI accelerator development

- Mixed-signal and low-power VLSI/ASIC implementation of neuromorphic processors.

- Hardware–software co-design and FPGA prototyping for emerging computing architectures.

- Application-driven integration of memristive hardware for intelligent edge devices.

Qualification

- Ph. D. in Electronics and Communication Engineering, Optoelectronics, Electrical Engineering, or any other related field relevant to the research.

Experience

- 1-2 years of Experience working in an Educational Institution Experience Required

Last Date to Apply November 30, 2026

📌 Postdoctoral Fellowship in Memristor-Based Neuromorphic Computing, In-Memory Computing, and CIM-Based AI Accelerators @Chennai
🏢 Amrita Vishwa Vidyapeetham
📍 Chennai