Research Associate in Brain-inspired Learning Accelerators

About us

Recently re-founded, the Department of Engineering is rapidly expanding into a world-class research and teaching department. Research currently focuses on information processing systems, robotics, telecommunications, and biomedical engineering, but we are looking to establish new research themes. 

This post will be affiliated with the newly established Centre for Intelligent Information Processing Systems within the department. 

About the role

The Centre for Intelligent Information Processing Systems (CIIPS) led by Professor Bipin Rajendran and Professor Osvaldo Simeone brings together interdisciplinary and diverse expertise synergistically to address future challenges in intelligent information systems, encompassing hardware-software co-design, nanoscale information systems, signal processing, information engineering, and quantum information processing. 

We are seeking a highly motivated and conscientious post-doctoral researcher to work on a project that involves the research, design, implement and validate the energy-efficient Spiking Neural Network architecture that leverages computing-in-memory principles.

The project will develop a low-power Neuromorphic Compute-in-Memory (CIM) ASIC prototype in nano-scale advanced CMOS technology based on spiking neural networks (SNNs) for both learning and inference for enhanced efficiency and reconfigurability. 

You will contribute to the architecture, design and implementation of the key components of the neuro-CIM that tightly integrates the CIM macros, spiking encoder, digital memory, top-controller, and peripheral interface to meet the energy, area, precision, and latency constraints.

The project will also involve the use of FPGA-based measurement and validation environment for the CIM processor system for benchmarking its accuracy and energy efficiency performances on various large datasets. You will also have the opportunity to mentor PhD and MSc students working in the group.

This is a full-time role (35 hours per week), and you will be offered a fixed term contract for 12 months, with the possibility of extension. 

About you

To be successful in this role, we are looking for candidates to have the following skills and experience:

Essential criteria

• PhD awarded (or near completion) in Electronic or Computer Engineering.
• Strong background in Analog/Mixed Signal Integrated Circuit (IC) design.
• Very good skills in HDL (Verilog, VHDL) and scripting languages
• Knowledge of commercial EDA tools (such as Cadence, Synopsys, or Mentor Graphics).
• Effective communication (oral and written) skills, ability to write research reports and papers in style accessible to academic audiences.
• Track record of high-quality research publications in peer reviewed conferences and/or journals.
• Ability to work independently and as part of a team on research programmes.

Desirable criteria

• Experience with hardware aware optimization of state-of-the-art machine learning models.
• Previous experiences in Tape-outs and Chip Testing.
• Experience with Low-power IC design and neuromorphic architectures.

Downloading a copy of our Job Description

Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the next page after you click “Apply”. This document will provide information of what criteria will be assessed at each stage of the recruitment process.

Further Information

We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.

To apply, please click the 'Apply' button, above.

If you encounter any technical difficulties while applying online, please email HR@kcl.ac.uk

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