Postdoctoral Research Associate in Smart and Green AI

at Northeastern University London, London, United Kingdom

Listed on EduAtlas: live school vacancies from schools’ own careers pages and public job services. Apply on northeastern.wd1.myworkdayjobs.com.

Salary

£43,555 to £46,195 a year

Closing date

Open until filled

Start

Not given in the advert

Type of post

Research

Visa sponsorship

The advert doesn’t say.
Northeastern University London holds a Home Office licence to sponsor Skilled Worker visas (rated A), on the register of 5 November 2026.

First seen

9 November 2026, on a public job listing

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The advert

About the Opportunity

Position Overview

D iscipline

Engineering

Faculty

Institute for Intelligent Networked Systems (INSI)

Location

London, Devon House (St Katherines Dock)

Term

1.5 years, fixed term, full-time

Salary Range

Grade 7, 34 (£43,555 - £46,195 per annum), dependent on experience.

Direct Reports

N/A

Reports to

Professor Bipin Rajendran

Benefits

The university supports staff maintaining a good work-life balance, offering: ( i ) flexible working and parental leave opportunities; ( ii ) an employee assistance programme which provides free, confidential advice on both home and work concerns, as well as optional private medical insurance; ( iii ) season ticket loans; and ( iv ) being part of the cycle-to-work scheme.

Start

January 2027

The Role

Northeastern University London invites applications for a Post-doctoral Research Associate ( PDRA) in Smart and Green AI to work with Professor Bipin Rajendran as part of his UKRI fellowship grant.

The successful candidate will work on the design, implementation and validation of hardware accelerator prototypes for state-of-the-art energy efficient and trustworthy AI models based on neuromorphic computing and In-Memory Computing (IMC) principles.

Core duties include:

• Contribute to the design, implementation, and evaluation of neuromorphic and in-memory hardware accelerator prototype boards for training and inference of state-of-the-art AI models.

• Develop algorithms, architectures, and hardware–software co-design methodologies for energy-efficient AI computation on neuromorphic and in-memory computing (IMC) platforms.

• Collaborate with cross-disciplinary teams spanning hardware design, AI/ML algorithms, information theory, and systems software to enable end-to-end system integration and validation.

• Publish high-quality research outcomes in leading journals and conferences in neuromorphic computing, AI hardware, and computer architecture.

• Support the supervision and mentoring of PhD and MSc students within the research group.

• Engage with industrial and academic collaborators to support joint research activities, technology transfer, and translational impact.

• Contribute to project management activities, including technical reporting, proposal development, and dissemination of research outcomes.

We particularly encourage applications from those belonging to groups underrepresented in UK higher education.

About the Institute

The Intelligent Networked Systems Institute (INSI) at NU London is a newly established transatlantic research hub focused on next-generation connectivity and intelligent computing and learning systems. The INSI London Hub acts as a bridge between the US and Europe, advancing interdisciplinary collaboration across continents. INSI is dedicated to addressing pressing challenges in telecommunications, artificial intelligence, quantum information, and information processing—all with the objective of creating a more efficient, connected, and secure world.

Person Specification Criteria

To undertake this role, the following should apply – should you not have the experience below, please do highlight where transferable skills would assist with you undertaking the role.

Qualifications

● PhD in Computer Science, Electronics or Computer Engineering or related quantitative field.

Key Criteria

● Strong publication record in neuromorphic hardware design demonstrated through publications in leading conferences and/or journals, with expertise extending beyond materials and device optimisation toward system-, architecture-, and algorithm-level innovation.

About Northeastern University London

Type

University

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