This PhD project at Kingston University focuses on the development of advanced methods for rapid and objective analysis of biomedical image and signal data. Hosted within the Faculty of Engineering, Computing and the Environment, the research aims to address key challenges in medical data interpretation by leveraging expertise in biophysics, biomedical engineering, electrical engineering, and electronic engineering. The successful candidate will work under the supervision of Professor D Wertheim, whose research includes the analysis of physiological signals and medical imaging, as evidenced by recent publications in pediatric research and respiratory monitoring. The project will involve designing and implementing computational techniques for processing and analyzing biomedical images and signals, with potential applications in clinical diagnostics, patient monitoring, and health informatics. Candidates will have the opportunity to engage with interdisciplinary research, collaborate with experts in engineering and medical science, and contribute to impactful advancements in healthcare technology. Funding for this position is available through the Kingston University Graduate School studentships competition for October 2026 entry. The studentship may cover tuition fees and provide a stipend, subject to the outcome of the competition. Applicants are encouraged to review the studentship details and eligibility criteria on the university's official website. Eligibility requirements include a strong academic background in biomedical engineering, electrical engineering, electronic engineering, biophysics, or a closely related field. Experience with image and signal processing, computational analysis, or medical data is highly desirable. All applicants must meet Kingston University's English language proficiency standards. The application deadline is March 4, 2026. Prospective students should consult the Graduate School Studentships information and the Faculty research webpage for guidance on preparing and submitting their application. This is an excellent opportunity for motivated individuals seeking to advance their research career in biomedical engineering and medical data analysis within a supportive academic environment.

This multidisciplinary PhD project at Kingston University, within the Faculty of Engineering, Computing and the Environment, aims to advance the understanding of the structure and nature of particulate matter particles. Building on previous research conducted at the university, the project will employ advanced data analysis techniques to investigate the physical and chemical characteristics of particulate matter, which is a critical concern in environmental science and public health. Particulate matter, often found in air pollution, consists of tiny particles that can have significant impacts on human health and the environment. The research will focus on characterizing these particles, exploring their composition, morphology, and behavior using a combination of experimental and computational methods. The project is highly interdisciplinary, drawing on expertise from environmental science, materials science, chemistry, and engineering. Students will have access to state-of-the-art laboratory facilities and analytical tools at Kingston University, and will be supported by a collaborative research environment. The project is supervised by Professor D Wertheim, an expert in the field, ensuring strong academic guidance and mentorship throughout the PhD journey. Applicants should possess a strong academic background in a relevant discipline, such as environmental science, materials science, chemistry, or engineering. Experience or interest in data analysis and multidisciplinary research is highly valued. The position is open to both UK and international candidates, though English language proficiency may be required for non-native speakers. Funding details are not specified in the current announcement, so applicants are encouraged to consult the university or project supervisor for potential funding opportunities. The application deadline is 4 March 2026, providing ample time for interested candidates to prepare their materials and reach out for further information. For more details and to apply, visit the official project page linked below.