Scholarships and funding

We will integrate microrobotics (CSEE) with stem cell and cancer biology (Life Sciences) to develop a novel microrobotics platform for efficient and effective delivery of therapeutic mesenchymal stem cells (MSCs).

These MSCs will be genetically modified to express an anti-cancer protein known as TRAIL that induces cancer cell death, leaving normal tissues unaffected.

Furthermore, to show proof of concepts in feedback swarm control of microrobots, we will be using an optical camera integrated with actuation system.

Lead department: School of Computer Science and Electronic Engineering (in collaboration with the School of Life Sciences)

Closing date: 31 March 2020

This interdisciplinary project aims to undertake PhD research in AI-powered intelligent systems for smart farming.

The researched systems are expected to provide growers with crop stress diagnostics and intervention strategies. It will increase crop productivity while protecting the environment.

Lead department: School of Computer Science and Electronic Engineering (in collaboration with the School of Life Sciences).

Closing date: 31 March 2020

This project aims to develop efficient error-correcting codes (ECCs) and random access techniques for DNA storage.

By viewing DNA storage as a communication channel, we will design robust ECCs and their associated decoding schemes to combat the errors (e.g., insertion, deletion, and substitution) that arise in DNA synthesis and sequencing processes.

Lead department: School of Computer Science and Electronic Engineering (in collaboration with the School of Life Sciences and Department of Mathematical Sciences).

Closing date: 31 March 2020

This studentship will research intelligent approaches to exercise training using wearable sensors and digital technologies that will help active individuals, athletes and people living with long term conditions to maximum their training and capacity over time.

Lead department: School of Computer Science and Electronic Engineering (in collaboration with the School of Sport, Rehabilitation and Exercise Sciences).

Closing date: 31 March 2020

This interdisciplinary studentship brings together the expertise of AI and machine learning with rehabilitation science also leveraging practical support from the Paediatric Physiotherapy Unit, Anglian Community Enterprise Community Interest Company.

The project is to develop a portable, marker-less motion capture system consisting of accelerometers and a video camera, and a gait assessment method using deep learning and data fusion techniques to automatically quantify the degree of walking impairment in children with Cerebral Palsy.

Lead department: School of Computer Science and Electronic Engineering (in collaboration with the School of Sport, Rehabilitation and Exercise Sciences)

Closing date: 31 March 2020

This project aims to develop an intelligent hybrid energy and transportation system in the presence of large-scale EVs and renewable energy with the-state-of-the-art game-theoretic and agent-based decision making, stochastic optimisation and deep learning methods.

Lead department: Department of Mathematical Sciences (in collaboration with the School of Computer Science and Electronic Engineering)

Closing date: 31 March 2020