PhD Study

AI for Multi-modal Healthcare

Department of Computer Science

A 3.5-year funded PhD studentship is available in the Department of Computer Science at University of Sheffield, working on the topic of multi-modal AI for healthcare. This project will focus on developing multi-modal AI models that can handle the complexities of medical data as well as the domain gap and knowledge gap across different scenarios, and further adapt to individual patient needs.

Deadline: Monday 10 June

Find out more information and apply here. 

Efficient and Robust Alignment of Large Language Models

Department of Computer Science

In this PhD, the student will explore developing new state-of-the-art methods for efficient and robust alignment of LLMs. Directions include: (i) data efficient fine-tuning and preference optimization; (ii) robustness to distribution shifts; and (iii) model compression.

Deadline: Monday 10 June

Find out more information and apply here.

Functional lung image synthesis using machine/deep learning: development, validation and application

School of Medicine and Population Health

This project seeks to overcome the limitations of traditional and functional lung imaging by developing a machine/deep learning framework to synthesise hyperpolarised gas MRI and dynamic contrast-enhanced perfusion MRI images from standard CT and proton MRI scans, enhancing diagnostic and monitoring capabilities for respiratory diseases.

Deadline: Wednesday 26 June

Find out more information and apply here.

 AI-driven Geographic Data Integration

Department of Computer Science

We are seeking a motivated PhD candidate to contribute to our efforts to develop innovative artificial intelligence-based tools for integrating and consolidating multidimensional geographic data from diverse sources.

Deadline: Sunday 30 June

Find out more information and apply here.

Causal Representation Learning in Computer Vision

Department of Computer Science

The primary objective of this research is to develop novel techniques for learning causal representations from visual data.

Deadline: Sunday 30 June

Find out more information and apply here.

Generative AI and flexible cognitive robots for discrete manufacturing

Department of Automatic Control and Systems Engineering

The aim of this PhD is to develop new human cognition inspired algorithms (such as Generative AI) that can learn how humans complete manufacturing tasks while dealing with variations in the environment as well as how they transfer learnt skills between tasks to solve problems. 

Deadline: Monday 15 July

Find out more information and apply here.

Energy-efficient AI Using Modular Deep Reservoir Computing

Department 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.

Find out more information and apply here. 

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 Sheffield, focusing on the development of intelligent vehicle safety strategies with a focus on brain injury prediction. 

Applications accepted all year round.

Find out more information and apply here. 

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.

Find out more information and apply here. 

Artificial intelligence and machine learning methods for model discovery in the social sciences

Department of Automatic Control and Systems Engineering

Many theories have been proposed for how problematic social phenomena - such as segregation, inequality, and clustering of unhealthy behaviours - emerge and change over time. But which theories are useful for understanding these phenomena and devising effective interventions to change them? This project will develop computationally efficient model discovery methods to enable a search for explanatory multi-level agent-based models that can be calibrated to - and validated against - such empirical phenomena.

Applications accepted all year round.

Find out more information and apply here. 

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 here. 

Machine Learning Digital Twins of Spintronic Neuromorphic Devices

Department of Computer Science

This project will develop the use of machine learning methods, particularly neural differential equations, for predicting the dynamics of experimental systems designed for neuromorphic computing. 

Applications accepted all year round.

Find out more information and apply here.