PhD studentship in Trustworthy Multimodal AI under Lightweight and Data-Efficient Architectures

Award Summary

100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate). Additional project costs will also be provided. 

Overview

Multimodal artificial intelligence (AI), which integrates diverse information sources including tabular, imagery, linguistic and acoustic data, has shown transformative potential in domains such as healthcare, environmental monitoring, and autonomous systems. However, most advances rely on large datasets and computationally intensive architectures that are impractical for scenarios constrained by limited data and resources for fine-tuning and deployment of large-scale models. What’s more, multimodal models are particularly vulnerable to data uncertainty, modality dropout, and noise propagation, which can degrade robustness and erode trust in model outcomes. This project aims to create a unified framework for building lightweight, data-efficient multi-modal AI models that can effectively handle uncertainty and generate reliable outputs. 

This is an exciting opportunity to work at the cutting edge of AI research. Your work will support safe, interpretable, and sustainable AI deployment for healthcare, environmental monitoring, and autonomous systems. You will have the freedom to shape the project direction, experiment with novel ideas, access state-of-the-art AI and computing facilities, receive tailored training and professional development, collaborate with experts across disciplines, and contribute to open-source tools that advance the wider AI community, and support long-term societal impact. 

We welcome applicants from background, including but not limited to computer science, data science, engineering or mathematics, who are passionate about machine learning and AI research. Strong analytical thinking, problem-solving skills, and the ability to engage with complex data challenges will be greatly valued. Experience with Python or AI frameworks is a plus but curiosity, creativity, and enthusiasm are equally important. You will join a supportive, interdisciplinary team at Newcastle University and play a key role in building responsible, trustworthy AI for the real-world applications, gaining hands-on experience with the latest AI technologies, contributing to knowledge transfer, and receiving opportunities to develop leadership, and research skills.  

Number Of Awards

1

Start Date

1st October 2026

Award Duration

4 years

Application Closing Date

18th February 2026

Sponsor

EPSRC  

Supervisors

Jingjing Zhang 

Wanqing Zhao 

Eligibility Criteria

We are adopting a contextual admissions process. This means we will consider other key competencies and experience alongside your academic qualifications. An example can be found here. 

A minimum 2:1 Honours degree or international equivalent in a subject relevant to the proposed PhD project is our standard entry, however we place value on prior experience, enthusiasm for research, and the ability to think and work independently. Excellent Analytical skills and strong verbal and written communication skills are also essential requirements. A Masters qualification may not be required if you have a minimum 2:1 degree or can evidence alternative experience in a work or research-based project. If you have alternative qualifications or experience, please contact us to discuss flexibilities and request an exemption. 

Applicants whose first language is not English require an IELTS score of 6.5 overall with a minimum of 5.5 in all sub-skills. International applicants may require an ATAS (Academic Technology Approval Scheme) clearance certificate prior to obtaining their visa and to study on this programme. 

How To Apply

For information on how to apply, please see Postgraduate Funding Search | Newcastle University

Contact Details

Jingjing.Zhang@newcastle.ac.uk You can also contact: doctoral.awards@ncl.ac.uk for independent advice on your application. 

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