Research Fellow in AI-Native Telecommunications Systems

Working Time: 37.5 hours per week

Post Type: Full Time

Contract Type: Fixed Term (Until 30 November 2028 - to complete specific time limited work)

Are you an ambitious researcher with expertise in artificial intelligence, large language models or retrieval-augmented generation, looking to tackle real-world healthcare challenges? Do you have experience developing and evaluating advanced AI systems and want to translate your research into technologies that can support earlier identification of respiratory disease? Would you like to lead the development of novel conversational AI solutions and real-world demonstrators as part of a major interdisciplinary research project?

We are seeking a highly motivated Research Fellow to join the EPSRC-funded AIRE project, developing next-generation AI systems for early identification of respiratory conditions through telephone-based interactions. You will work at the intersection of artificial intelligence, telecommunications and digital health, contributing to the design of conversational AI capable of conducting clinical history-taking, analysing speech and language signals, and supporting earlier intervention for respiratory disease.

Working with an interdisciplinary team of engineers, computer scientists and healthcare professionals, you will develop and evaluate novel approaches for conversational AI, multimodal machine learning, large language models, speech analytics and clinical decision support. The project aims to improve access to healthcare through scalable, accessible telephone-based assessment technologies, helping identify individuals who may benefit from further clinical investigation.

You should have a strong background in one or more of the following areas: artificial intelligence, machine learning, natural language processing, speech processing, data science, digital health, telecommunications, or software engineering. This is an exciting opportunity to contribute to impactful research with clear societal benefit while working in a collaborative environment at the forefront of AI-enabled healthcare innovation.  

This role will be based on the University campus, with scope for it to be undertaken in a hybrid manner. We are open to discussing flexible working arrangements. 

To explore the post further or for any queries you may have, please contact: 

Dr. Maryam Hafeez, Associate Professor in Communication Systems and Networks

Email: M.Hafeez@leeds.ac.uk

Please note that this post may be suitable for sponsorship under the Skilled Worker visa route but first-time applicants might need to qualify for salary concessions. For more information, please visit the Government’s Skilled Worker visa page.

For research and academic posts, we will consider eligibility under the Global Talent visa. For more information, please visit the Government’s page, Apply for the Global Talent visa

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