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Aston University

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PhD in Multimodal Artificial Intelligence for Medical Imaging and Clinical Decision Support Aston University in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Funded PhD project. This project covers tuition fees only at the Home or Overseas rate; no stipend or living allowance is mentioned.

Deadline

Sep 15, 2026

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Country

United Kingdom

University

Aston University

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Keywords

Computer Science
Biomedical Engineering
Electrical Engineering
Medical Imaging
Artificial Intelligence
Computer Vision
Digital Health
Medical Science
Explainable Ai
Clinical Decision Support
ML

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About this position

PhD opportunity: Multimodal Artificial Intelligence for Medical Imaging and Clinical Decision Support at Aston University in Birmingham, United Kingdom.

This funded PhD project sits at the intersection of artificial intelligence, medical imaging, machine learning, computer vision, multimodal learning, foundation models, and explainable AI. The project aims to develop next-generation AI methods for analysing medical images and healthcare data to support biomarker discovery, disease prediction, patient stratification, prognosis prediction, and clinical decision support.

The research will explore how to integrate heterogeneous data sources such as medical images, clinical records, physiological measurements, and other healthcare datasets. It will focus on robust and clinically meaningful AI systems that can generalise across diverse patient populations and healthcare settings. Potential research directions include subtle imaging biomarker detection, multimodal data fusion, model generalisation, and reliable diagnostic/prognostic decision-making.

Supervisor: Dr Alireza Rastegarpanah (Aston University). Contact: [email protected].

Funding: This project covers tuition fees only at the Home or Overseas rate. No stipend is mentioned.

Eligibility: Applicants should have a relevant bachelor’s degree with First Class or 2.1, or a relevant bachelor’s degree plus a relevant master’s degree with Merit or higher. Strong Python programming, data analysis, machine learning, scientific computing, or algorithm development experience is expected. Desirable experience includes deep learning, medical image analysis, multimodal learning, PyTorch/TensorFlow/Scikit-learn, and prior research activity.

Application materials: transcripts and certificates, a research statement, a personal statement, two academic referees, English language evidence, and a passport copy. Incomplete applications will be rejected.

Location: Birmingham, United Kingdom.

Deadline: 2026-09-15.

Funding details

Funded PhD project. This project covers tuition fees only at the Home or Overseas rate; no stipend or living allowance is mentioned.

What's required

Applicants should have, or expect to achieve, either a relevant bachelor's degree with First Class or 2.1, or a relevant bachelor's degree with First Class or 2.1 plus a relevant master's degree with Merit or higher. Equivalent international qualifications accepted by Aston University may also be considered. Candidates must have strong programming skills, especially in Python, and experience in data analysis, machine learning, scientific computing, or algorithm development. Strong analytical and problem-solving ability, independence, and a genuine interest in applying AI to healthcare are required. Desirable experience includes machine learning, deep learning, computer vision, medical image analysis, multimodal learning, foundation models, data science, statistical modelling, healthcare analytics, robotics, autonomous systems, mixed reality, digital twins, or trustworthy and explainable AI, plus familiarity with PyTorch, TensorFlow, or Scikit-learn and evidence of research activity.

How to apply

Prepare a complete application with all supporting documents, including transcripts and certificates, a research statement, a personal statement, two academic referees, evidence of English language ability, and a passport copy. Submit through the Aston University application process for this PhD project. Incomplete applications will be automatically rejected.

More information can be found here

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