PhD Studentship: Deep Learning and Innovative Optical Microscopy to Uncover Cancer Electrostatics

Funding: Fully funded for UK students; competitive funding for international students | Start Date: October 2025

The fight against life-threatening diseases such as cancer demands cutting-edge technology to allow a deep understanding of how living systems function at the molecular and cellular levels. One crucial—but often overlooked—aspect is electrostatic charge, which influences how cells divide, migrate, and interact with their surroundings. Current tools for measuring these properties have significant limitations, especially with delicate 3D biological samples.

This PhD project will revolutionise cancer research by creating a transformative imaging tool to map electrostatic charge in 3D living environments. Optical trapping (a laser-based technique for manipulating microscopic particles) will enable the delicate mapping of electrostatic forces and electric fields in living cells. Combined with AI-driven analysis, deep learning will enhance the sensitivity and speed of measurements as well as expose hidden patterns of cancer electrostatics. This approach promises to uncover how changes in electrostatics influence cancer progression, providing a detailed contrast between cancerous and normal cells at the cellular and subcellular levels. The outcomes of this research will not only advance our understanding of cancer's electrostatics but also facilitate the development and testing of new treatments aimed at manipulating cancer electrostatic properties.

Why is this important? You will develop a state-of-the-art imaging tool, gain expertise in optical engineering, AI, and biophysics, and apply them to real-world challenges in cancer research. The project is highly interdisciplinary, offering opportunities to collaborate with leading experts in optics, bio-photonics, and biomedical science. This role is ideal for someone eager to bridge engineering and biology in a rapidly evolving research field.

Who are we looking for? We are seeking a highly motivated candidate with a strong academic background (1^st or 2:1 degree) in biomedical engineering, physics, biophysics, computer science, electronics, or a related field. Experimental skills, programming (Python or MATLAB) and data analysis are essential skills, with experience in optical systems, deep learning, or nanotechnology as a plus. Creativity, problem-solving ability, and a passion for interdisciplinary research are key to success.

Funding and Eligibility: The studentship is fully funded for UK students, covering tuition fees and a tax-free stipend (£19,237/year). Competitive funding for international students may be available.

How to Apply: Informal enquires can be directed to Dr Sidahmed Abayzeed (sidahmed.abayzeed2@nottingham.ac.uk) and Prof. Amanda Wright (amanda.wright@nottingham.ac.uk)

To apply, please email us the following:

• A brief statement of your research interests and motivation for applying.
• A CV including degree classification (actual or expected), academic transcripts, publications (if any), and contact details for two academic referees.
• A sample of technical writing such as a dissertation or project report.

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