PhD Study
The University of Sheffield offers various PhD programmes with different opportunities to study Artificial Intelligence.
PhD opportunities
Shifting the paradigm: machine-assisted scholarly digital editing
Digital Humanities Institute
This PhD project investigates how AI and machine learning can transform scholarly digital editing—streamlining editorial workflows and reimagining digital editions beyond traditional print formats. Candidates will explore tools such as NLP, large language models, and data visualisation to enhance and innovate the presentation of historical or cultural texts. Applicants are invited to bring their own case studies and subject expertise to advance the field of digital editing.
Applications accepted all year round.
Find out more information and apply here.
Process Induced Neural Networks for Environmental Data Analysis and AI for Data Adjustments
Centre for Doctoral Training in Green Industrial Futures
A funded PhD opportunity within the Centre for Doctoral Training in Green Industrial Futures (CDT-GIF), exploring the use of AI and Process Induced Neural Networks (PINNs) to analyse complex environmental energy data. In partnership with Toyota Motor Europe, this project supports the transition to net zero through advanced data-driven monitoring. Includes training across four leading UK universities and international research opportunities.
Applications accepted all year round.
Find out more information and apply here.
Two Fully-funded PhD Studentships in Spoken Language Technologies
University of Sheffield
Two candidates are sought for interdisciplinary Speech and Language Technologies (SLT) projects. One project focuses on making UK Parliament proceedings more accessible for better public and journalistic engagement. Another project aims to improve AI's understanding of conversations by incorporating paralinguistic cues and participant context. The third project explores language development in AI agents with sensory and physical interactions to better understand human language and improve autonomous agents.
Applications accepted all year round.
Find out more information and apply here.
Urban Green Infrastructure Planning for Connectivity, Sustainability, biodiversity and multifunctionality
School of Electrical and Electronic Engineering
This self-funded PhD explores using digital planning and Green Infrastructure (GI) to tackle climate change and biodiversity loss in urban areas. Research focuses on ecological connectivity, GI multifunctionality, and applying AI and digital twins for sustainable urban planning. This opportunity offers a chance to contribute to innovative solutions for urban sustainability within an interdisciplinary research group.
Applications accepted all year round.
Find out more information and apply here.
Automated Detection and Analysis of Cancers using Artificial Intelligence
School of Clinical Dentistry
The aim of this project is to investigate the use of artificial intelligence and machine learning in automated detection and segmentation of cancer and its microenvironment for downstream prognostic analysis. Analysis of histomorphological as well as molecular/genomic features will also be performed. The findings from this study have the potential to significantly influence diagnostic practice and patient stratification in the future.
Applications accepted all year round.
Find out more information and apply here.
AI for Multi-modal Healthcare
School of Computer Science
A 3.5-year funded PhD studentship is available at the University of Sheffield, focusing on multi-modal AI for healthcare. The project aims to develop AI models capable of handling complex medical data, addressing domain and knowledge gaps, and adapting to individual patient needs, with potential emphasis on large language models, explainable AI, and identifying pitfalls in current AI models through adversarial machine learning.
Applications accepted all year round.
Find out more information and apply here.
Machine tool dynamics-based digital twins for real-time monitoring of cutting tool conditions in smart manufacturing
School of Electrical and Electronic Engineering
This PhD project focuses on advancing a novel, model feature-based tool condition monitoring (TCM) technique to meet the needs of real-time monitoring in complex machining environments. By collaborating with industry leaders and the Advanced Manufacturing Research Centre (AMRC) in Sheffield, the research aims to improve the adaptability and efficiency of TCM systems, moving them to higher Technology Readiness Levels (TRLs) for practical industrial applications.
Applications accepted all year round.
Find out more information and apply here.
Adaptive Learning in Brain-Robot Interactions
School of Electrical and Electronic Engineering
This project aims to develop a non-invasive brain-machine interface (BMI) that allows a user to direct a semi-autonomous robot to perform different tasks through brain signals.
Applications accepted all year round.
Find out more information and apply here.
Joining up Solar and Stellar Flare Energy Estimates
School of Electrical and Electronic Engineering
We seek candidates to advance solar-stellar flare research by addressing challenges in energy estimation methodologies and aligning solar and stellar observational techniques. This project aims to validate new estimation techniques, integrate machine learning, analyse energy frequency mismatches, study "solar-like" stars, and update long-term super-flare probability estimates for our Sun.
Applications accepted all year round.
Find out more information and apply here.
AI-enabled digital technologies for the resilient operation of power systems
School of Electrical and Electronic Engineering
Are you interested in power system research for the future power grid operation? We have a recent PhD project opportunity at The University of Sheffield, a World leading Russell Group university in the UK.
Applications accepted all year round.
Find out more information and apply here.
Physics informed learning for high fidelity medical simulators
School of Mechanical, Aerospace and Civil Engineering
This project, led by Prof. Dogramadzi at Sheffield Robotics, aims to use physics-informed machine learning and high-fidelity simulations to optimise medical device design and performance. By modelling complex interactions between devices and the human body, it seeks to bridge the gap between simulation and real-world applications, focusing on a common surgical or endoscopic procedure with clinical specialist collaboration.
Applications accepted all year round.
Find out more information and apply here.
Development of a Wearable Sensor System and AI-Driven Analysis for Objective Bruxism Assessment
School of Clinical Dentistry
This PhD project aims to develop and validate a novel wearable sensor system for comprehensive bruxism assessment.
Applications accepted all year round.
Find out more information and apply here.
Automated Detection and Analysis of Cancers using Artificial Intelligence
School of Clinical Dentistry
The aim of this project is to investigate the use of artificial intelligence and machine learning in automated detection and segmentation of cancer and its microenvironment for downstream prognostic analysis. Analysis of histomorphological as well as molecular/genomic features will also be performed.
Applications accepted all year round.
Find out more information and apply here.
Developing AI Controlled Granulation Process for Formulated Chemicals
School of Chemical, Materials and Biological Engineering
The aim of this project is to use Industry 4.0 technologies including machine learning and artificial intelligence (AI) to develop digital and soft sensors to predict product properties and optimise process in real-time for manufacturing functional chemical and/or pharmaceutical products
Applications accepted all year round.
Find out more information and apply here.