King's College London

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 funded by ARIA that involves the design, implementation and validation of accelerators for training large language models (LLMs) based on neuromorphic computing and In-Memory Computing (IMC) principles.

The project will develop a low-power Neuromorphic In-Memory Computing (IMC) ASIC prototype in nano-scale advanced CMOS technology based on spiking neural networks (SNNs) for both training and inference of of LLMs.

You will also have the opportunity to mentor PhD and MSc students working in the group.

This is a full-time contract (35 hours per week), and you will be offered a fixed term contract until 15 May 2026.

About you

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

Essential criteria

1.       PhD awarded (or near completion) in Electrical/Electronic or Computer Engineering.

2.       Strong publication record in machine learning, including in top-tier machine-learning conferences and journals

3.       Experience in presenting research results and/or tutorials in top-tier conferences and workshops.

4.       Effective communication (oral and written) skills, ability to write research reports and papers in style accessible to academic audiences

5.       Previous experience with probabilistic and/or Neuromorphic machine learning models

6.       Ability to work independently and as part of a team on research programmes

Desirable criteria

1.       Previous experience with co-optimisation of AI models for Hardware implementation

2.       Previous experience with designing novel training algorithms

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 Now”. This document will provide information of what criteria will be assessed at each stage of the recruitment process.

*  Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.

Further Information

We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community.

We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King's.

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 find out how our managers will review your application, please take a look at our ‘How we Recruit’ pages.