Research Associate in Analogue AI Accelerators

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.

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 join a very collaborative, interdisciplinary, and friendly research group at King's College London led by Professor Bipin Rajendran.

The group at King's is part of a consortium developing multiprocessor systems-on-chip with advanced nanoscale in-memory neural processing units that are funded by the Horizon Europe Programme. The consortium team will develop an advanced Multi-Processor System on Chip prototype in FD-SOI 28nm CMOS technology that tightly integrates an Analog In-Memory Computing (AIMC) unit based on embedded phase-change memory technology. As part of this project, you will have the opportunity to collaborate with world-leading researchers from industries (including IBM Research and ST Microelectronics) and universities in Europe.

You will contribute to the architecture and design of the neural processing unit that comprises one or more AIMC tiles. The project will also involve the use of a Pytorch-based simulation environment for network optimisation that is incorporating the statistical behavioural features of AIMC hardware.

You will also further develop hardware-aware training methodologies optimized for inference with the architecture and collaborate with project partners involved in the experimental demonstrations of various Machine Learning use cases in the new hardware. You will also have the opportunity to mentor PhD and MSc students working in Professor Rajendran's group.

This is a full-time post (35 hours per week), offered on a fixed-term contract from 1st September 2025 to 28th February 2026 (dependent on further funding, extension to October 2026 possible). An earlier start date may be considered, subject to candidate availability.

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

Essential criteria

1.       PhD awarded in Electrical or Computer Engineering

2.       Knowledge about Deep Learning algorithms, models, and their optimization techniques

3.       Knowledge of TensorFlow, PyTorch, etc.

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

5.       Experience with developing and optimizing deep learning models

6.       Track record of high-quality research publications in peer reviewed conferences and/or journals.

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

Desirable criteria

1.      Experience with hardware aware optimization of state-of-the-art machine learning models.

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 page. 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. 

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.

As part of this commitment to equality, diversity and inclusion and through this appointment process, it is our aim to develop candidate pools that include applicants from all backgrounds and communities.

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.