PhD Studentship: Imaging with AI Integration for Early and Continuous Health Diagnostics and Monitoring

Why this research matters

Cancer remains the leading cause of death globally. Early detection is critical to improving survival rates, but traditional diagnostic methods such as CT and MRI are costly, inaccessible in underserved areas, and pose health risks due to ionising radiation. In rural and disadvantaged communities, screening participation is less than 50%, leaving many cases undiagnosed.

Microwave Imaging (MWI) offers a revolutionary solution. It is safe, portable, cost-effective, and enables frequent, radiation-free monitoring of critical conditions such as cancer, stroke and infections. This research aligns with the NHS Core20PLUS5 strategy, which aims to reduce health disparities and bring life-saving diagnostics closer to underserved populations.

What the research involves

This project will develop an AI-integrated MWI system specifically for thoracic cancer and lesion/infection detection. The plan involves developing an innovative system with advanced microwave sensors, cutting-edge imaging algorithms, and a compact, portable design tailored for pre-hospital and community-based settings such as ambulances, pharmacies, and outreach centres.

Key research objectives include:

1. High-Sensitivity Sensors: Developing sensors capable of differentiating malignant tissues which have up to three times higher dielectric contrast than healthy tissues.
2. Advanced Imaging Algorithms: Designing conductivity- and phase-weighted algorithms for accurate and high-resolution imaging of thoracic tissues.
3. AI Integration and Portability: Creating customised AI models for improved diagnostic accuracy.
This interdisciplinary project spans biomedical engineering, applied electromagnetics, and AI, addressing a major global healthcare challenge.

Supervision and support

You will join a dynamic, multidisciplinary research team led by Dr Behnaz Sohani and Professor Will Whittow, a specialist in healthcare technologies, MWI, and AI. The team is committed to providing a collaborative and supportive environment, where you will have access to state-of-the-art facilities. 

Skills and career opportunities

This project will develop your expertise in:

• Sensor designs tailored for medical applications.
• Advanced medical imaging technologies.
• AI-driven image reconstruction and diagnostics.
• Translational research with real-world healthcare applications.

These skills are highly valued in academia, healthcare technology development and industry.

How to Apply:

Applications should be made online via the above ‘Apply’ button. Under programme name, select ‘Mechanical and Manufacturing Engineering/Electronic, Electrical & Systems Engineering’ and quote the advert reference number FP-BS-2025 in your application.  

To avoid delays in processing your application, please ensure that you submit your CV and the minimum supporting documents.  

The following selection criteria will be used by academic schools to help them make a decision on your application. 

English language requirements:

Applicants must meet the minimum English language requirements. Further details are available on the international website (http://www.lboro.ac.uk/international/applicants/english/).

Funding Details

Additional Funding Information

The studentship is for 3 years and provides a tax-free stipend of £19,237 per annum for the duration of the studentship plus university tuition fees.

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