Available Projects
The project list below helps self-funded and externally sponsored applicants (scholarship) connect with a prospective supervisor.
Applications are welcome from those who can support themselves or have funding already arranged. Such applications will go through the same level of academic assessment. Please see the fee arrangementsLink opens in a new window for PGR students.
Video analysis of the behaviour of micro-organisms: development of automated behaviour monitoring techniques
Micro-organisms exhibit complex behaviours that provide valuable insights into biological processes, environmental responses, and cellular health. This project will develop automated video analysis techniques to detect, quantify, and track microorganism behaviour. Combining computer vision, image processing, and AI, the research will enable high-throughput, objective behavioural monitoring, supporting advances in biotechnology, microbiology, environmental science, and biomedical research.
Primary supervisor: Christopher James - c.james@warwick.ac.uk
Project detail:
The behaviour of micro-organisms provides important information about their physiology, health, environmental responses, and interactions with surrounding systems. Traditional methods for observing and characterising microbial behaviour often rely on manual inspection of microscopy videos, which can be time-consuming, subjective, and difficult to apply at scale. Recent advances in imaging technologies have enabled the collection of large volumes of high-resolution video data, creating opportunities for the development of automated approaches that can extract meaningful behavioural information rapidly and consistently.
This PhD project will focus on the development of novel video analysis techniques for the automated monitoring and quantification of microorganism behaviour. The research will explore how computer vision, image processing, machine learning, and artificial intelligence can be combined to identify, track, and classify the movement and interactions of micro-organisms within complex environments. The resulting tools will support objective and reproducible analysis of behavioural patterns that may otherwise be difficult to detect through conventional observation.
Key challenges include accurately detecting individual organisms in noisy image sequences, tracking movement over time, distinguishing between behavioural states, and analysing interactions between multiple organisms. The project will investigate advanced algorithms capable of robust performance under varying imaging conditions and across different microorganism species. Opportunities may also exist to develop methods for extracting quantitative behavioural metrics such as motility, navigation strategies, population dynamics, and responses to external stimuli.
The research sits at the interface of biomedical engineering, computer vision, artificial intelligence, microbiology, and quantitative biology. The successful student will gain expertise in image analysis, machine learning, computational modelling, and biological data science while working on a highly interdisciplinary problem with broad scientific relevance. Access to microscopy datasets and modern computational tools will provide opportunities to develop solutions with strong translational and research impact.
Automated behaviour monitoring has the potential to transform how microbial systems are studied in both laboratory and applied settings. Applications span biomedical research, biotechnology, environmental monitoring, drug discovery, synthetic biology, and industrial bioprocessing. By enabling rapid and objective analysis of microorganism behaviour, this project will contribute to a deeper understanding of biological systems and support the development of next-generation tools for quantitative life science research.
How to apply for admission: www.warwick.ac.uk/pgrengineering
The University of Warwick provides an inclusive working and learning environment, recognising and respecting every individual’s differences. We welcome applications from individuals who identify with any of the protected characteristics defined by the Equality Act 2010.