At a Glance
- Tasks: Join a collaborative team to design advanced neural processing units and optimise deep learning models.
- Company: King's College London is a leading research institution, expanding its engineering department with innovative projects.
- Benefits: Enjoy a competitive salary, mentorship opportunities, and the chance to work with top industry partners.
- Other info: This role offers a fixed-term contract with potential for extension and a supportive, inclusive work environment.
- Why this job: Be part of cutting-edge research in AI, contributing to impactful projects with global experts.
- Qualifications: PhD in Electrical or Computer Engineering, knowledge of deep learning, and experience with TensorFlow or PyTorch required.
The predicted salary is between 37800 - 47800 € per year.
Organisation/Company KINGS COLLEGE LONDON Research Field Architecture Engineering Researcher Profile Leading Researcher (R4) Country United Kingdom Application Deadline 23 Jul 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description
About us
Recently re-founded, the Department of Engineering is rapidly expanding into aworld-class research and teaching department.
Researchcurrently 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 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.
About you
To be successful in this role, we are looking for candidates to have the following skills and experience:
- PhD awarded in Electrical or Computer Engineering
- Knowledge about Deep Learning algorithms, models, and their optimization techniques
- Knowledge of TensorFlow, PyTorch, etc.
- Effective communication (oral and written) skills, ability to write research reports and papers in style accessible to academic audiences
- Experience with developing and optimizing deep learning models
- 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
- 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.
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.
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.
Grade and Salary:£47,882 per annum, including London Weighting Allowance
Job ID:119925
Close Date:23-Jul-2025
Contact Person:Bipin Rajendran
Contact Details:bipin.rajendran@kcl.ac.uk
Research Associate in Analogue AI Accelerators employer: European Commission
At King's College London, we pride ourselves on fostering a collaborative and inclusive work environment that encourages innovation and professional growth. As a Research Associate in Analogue AI Accelerators, you will have the unique opportunity to work alongside world-class researchers and industry leaders, contributing to cutting-edge projects while mentoring the next generation of engineers. Our commitment to diversity and inclusion ensures that every employee feels valued and connected within our vibrant academic community in the heart of London.
StudySmarter Expert Advice🤫
We think this is how you could land Research Associate in Analogue AI Accelerators
✨Tip Number 1
Network with professionals in the field of Electrical and Computer Engineering, especially those involved in deep learning and hardware optimization. Attend relevant conferences or workshops where you can meet researchers from King’s College London and other institutions.
✨Tip Number 2
Familiarise yourself with the latest advancements in Analog In-Memory Computing and related technologies. This knowledge will not only help you during interviews but also demonstrate your genuine interest in the research area.
✨Tip Number 3
Engage with the work of Professor Bipin Rajendran and his team by reading their recent publications. Understanding their research focus and methodologies will allow you to tailor your discussions and show how your skills align with their projects.
✨Tip Number 4
Prepare to discuss your experience with PyTorch and TensorFlow in detail. Be ready to share specific examples of how you've optimised deep learning models, as this will be crucial for demonstrating your fit for the role.
We think you need these skills to ace Research Associate in Analogue AI Accelerators
Some tips for your application 🫡
Understand the Role:Read the job description thoroughly to grasp the specific skills and experiences required for the Research Associate position. Pay attention to the emphasis on deep learning algorithms, hardware-aware optimization, and effective communication.
Tailor Your CV:Customise your CV to highlight relevant experience in Electrical or Computer Engineering, particularly focusing on your PhD work, publications, and any projects related to deep learning and neural processing units.
Craft a Strong Supporting Statement:Write a compelling supporting statement that clearly outlines how your background aligns with the essential criteria listed in the job advert. Use specific examples from your research to demonstrate your expertise and achievements.
Proofread and Format:Before submitting your application, ensure that your documents are free of errors and formatted professionally. A well-organised application reflects your attention to detail and professionalism, which is crucial for a research role.
How to prepare for a job interview at European Commission
✨Showcase Your Research Experience
Be prepared to discuss your previous research projects in detail. Highlight any publications or presentations you've made, especially those related to deep learning or hardware-aware optimisation, as these are crucial for the role.
✨Demonstrate Technical Proficiency
Familiarise yourself with the tools and technologies mentioned in the job description, such as TensorFlow and PyTorch. Be ready to explain how you've used these in past projects and how you can apply them to the new role.
✨Communicate Clearly
Effective communication is key. Practice explaining complex concepts in a way that is accessible to both technical and non-technical audiences. This will be important when discussing your work with team members and stakeholders.
✨Prepare Questions for the Interviewers
Think of insightful questions to ask about the research group, ongoing projects, and future directions. This shows your genuine interest in the position and helps you assess if the role aligns with your career goals.
