Research Fellow in Efficient Machine Learning Systems

Updated: about 2 months ago
Location: Southampton, ENGLAND
Job Type: FullTime
Deadline: 17 May 2024

30 Apr 2024
Job Information

Research Field

Computer science
Researcher Profile

Recognised Researcher (R2)
First Stage Researcher (R1)
Established Researcher (R3)

United Kingdom
Application Deadline

17 May 2024 - 00:00 (UTC)
Type of Contract

Job Status

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?


Offer Description

Digital Health & Biomedical Engineering

Location:  Highfield Campus
Salary:   £36,024 to £40,521 Per annum
Full Time Fixed Term for 24 months
Closing Date:  Friday 17 May 2024
Interview Date:   To be confirmed
Reference:  2610524FP-R

We are recruiting an outstanding team of researchers from AI, Edge Computing, and Digital Design, to work with us on achieving Perfect Recollection for Clearer Insight” project’s ambitious objectives. You will work with Dr Jagmohan Chauhan and Dr Alex Weddell in ECS in collaboration with teams at the University of Cambridge,  University of Manchester,  Turing Institute, and HMGCC. 

You will develop new low-power systems and ML algorithms to significantly extend the capabilities of onboard AI when used in small satellites for earth observation applications. This project aims to enhance the performance of sensing systems by leveraging very large memories while extracting precise and nuanced insights from data on edge devices that are constrained by power and communication. Our objective is to develop memory-centric systems capable of extracting larger volumes of valuable information from sensor data in a timely and energy-efficient manner. The research will innovate at software-hardware level. You will be writing research papers, submitting project deliverables with project collaborators and travel to academic conferences and project meetings to present the work.   

Successful candidates must hold (or close to completing) a PhD in a relevant subject. Knowledge and experience in computer vision is required. Experience of efficient ML techniques, edge AI hardware platforms, low-power computing, earth observation is desirable.  They will have excellent programming skills (Python, C++, etc.) with track record of publications in top conferences/journals such as CVPR, ICML, MobiCom, and DAC. 

Note: Successful candidate is required to undergo security checks from NSTIx before appointment confirmation.  

Why us? 

University of Southampton is a top university (1% of world universities; top 10 UK). ECS is one of the top CS departments in the UK. Southampton is a vibrant city by the water, a hub for technology companies; close to London.  

We have a positive and vibrant environment.  You will have an opportunity to work on cutting-edge technology and publish in top-tier conferences/journals.  There will be opportunities to visit the partner institutions while working closely with them. We  have a large network of collaborations with academics at Imperial, Cornell, and industrial labs such as Samsung-AI, Bell Labs for you to foster further collaborations.   

Check out the staff benefits  and why you should join us at The University of Southampton! 

*Applications for Research Fellow positions will be considered from candidates who are working towards or nearing completion of their PhD. The title of Research Fellow will be applied upon successful completion of the PhD. Prior, title of Senior Research Assistant is applicable.   

We believe EDI is fundamental to making the UoS a welcoming, vibrant and successful organisation. Having a diverse workforce, inclusive of people of all ages and beliefs, from different racial backgrounds, educational and social backgrounds open up a wealth of possibilities, makes us more creative and accelerates our impact on society. We welcome applicants that value diversity of our community and are willing to play their part in supporting the mission of inclusivity.

Additional Information
Work Location(s)
Number of offers available
United Kingdom

Where to apply




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