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Integrating machine-learning techniques to learn interactions between structural components and physical domains

School of Mechanical, Aerospace and Civil Engineering

The project aims at evaluating the performance of different machine-learning methods for the learning the desired interactions and for defining digital twins of structures. The methods may span from simple techniques to more complicated deep-learning techniques and the main objective is to integrate different types of data and even various types of models in the inference procedure. 

Deadline: Friday 31 January 2025

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Using Artificial Intelligence to Reveal the Signature of Development in Organismal Colour Pattern Designs

Yorkshire Bioscience Doctoral Training Partnership

The primary aim of this project is to leverage cutting-edge image analysis and AI tools to test for the signature of developmental processes and constraints in shaping organismal colour pattern design. These tools will be applied to large collections of images capturing complex colour pattern variation across several animal groups (e.g. birds, butterflies, fish, mammals) to provide insight into the developmental pathways and constraints underlying colour pattern phenotypes.

Deadline: Friday 14 March 2025

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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.

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AI for Multi-modal Healthcare

School of Computer Science

A 3.5-year funded PhD studentship is available at the University of ºù«Ӱҵ, 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.

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Machine Learning for Resilient Operation of Cybersecurity Systems

School of Electrical and Electronic Engineering

Are you interested in machine learning and data science and their application to cybersecurity? We have a PhD project fully funded by the DSTL (Defence Science and Technology Laboratory) at ºù«Ӱҵ, part of the prestigious UK Russell Group of Universities in the UK.

Applications accepted all year round.

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 ACS-99-OPEN - 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 ºù«Ӱҵ, 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.

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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.

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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.

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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 ºù«Ӱҵ, a World leading Russell Group university in the UK.

Applications accepted all year round.

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Machine Learning for radiative transfer applications in multidimensional flare simulations

School of Electrical and Electronic Engineering

This project will combine the strengths of the University of ºù«Ӱҵ’s ACSE department (expertise in Machine Learning), with the world leading 1D flare modelling expertise of NASA Goddard Space Flight Center.

Applications accepted all year round.

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Physics informed learning for high fidelity medical simulators

School of Mechanical, Aerospace and Civil Engineering

This project, led by Prof. Dogramadzi at ºù«Ӱҵ 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.

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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.

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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

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.

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Energy-efficient AI Using Modular Deep Reservoir Computing

School of Computer Science

This project aims to explore how diverse properties in recurrent neural networks can be used to create reservoir computing architectures able to tackle challenging real-world tasks.

Applications accepted all year round.

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Real-Time Brain Injury Prediction and Protection Framework for Intelligent Vehicles

Department of Mechanical Engineering

We are seeking a highly motivated PhD candidate to join our research project at the University of ºù«Ӱҵ, focusing on the development of intelligent vehicle safety strategies with a focus on brain injury prediction. 

Applications accepted all year round.

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Statistics and AI for Engineering and Smart Manufacturing

School of Mathematics and Statistics

We are thrilled to announce an exceptional PhD opportunity in the dynamic fields of Statistics and Artificial Intelligence, specifically tailored for Engineering and Smart Manufacturing. This project is designed for candidates eager to explore and expand the realms of statistical analysis and reliable AI in industrial pipelines, with a special emphasis on smart manufacturing and electronic design automation (EDA).

Applications accepted all year round.

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Online discussion; augmenting argumentation with chatbots

Department of Psychology

Argumentation - the systematic exchange of reasoning supporting or undermining an idea - enhances communication between individuals. Unreliable chains of thought are weeded out, reliable ones survive. Striking evidence for this is that reasonings tasks which provoke systematic errors when considered by individuals choice can be solved correctly by small groups, if they are given time for discussion. Chatbots with natural language processing create an opportunity to have artificial agents interact with group deliberation, and make it more effective. In this way, the strengths of human and artificial intelligence can augment each other

Applications accepted all year round.

Find out more information and apply .