Job Description

Job Description:

Project Focus: Develop data‑efficient AI methods for medical imaging with application to cancer detection.
Research Objectives: Create AI systems that learn reliably from limited, inconsistent, or expensive‑to‑label data.
Research Area: Explore new learning strategies including reinforcement learning and meta‑learning (no prior experience required).
Project Application: Work on real‑world image‑based cancer detection problems, supported by clinical collaborators.
Collaboration: Joint work with the Digital Environment Research Institute (DERI) and Barts Cancer Institute (both QMUL).
Responsibilities: Conduct original PhD research, publish findings, participate in academic activities at QMUL’s Centre for Bioengineering.
Duration: Full PhD programme (typically 3–4 years), fully funded.
Eligibility:

Academic Background: Undergraduate degree (or equivalent) in engineering, computer science, biomedical engineering, or related field.
GPA/Grade: Competitive academic record (typically high 2:1 or equivalent).
Experience: No prior research experience in reinforcement/meta‑learning required; strong analytical and programming skills preferred.
Nationality: Open to international students (UK tuition fees covered for eligible candidates).

Requirements:

Strong programming skills (Python, machine learning frameworks).
Good understanding of AI/ML principles and willingness to learn advanced techniques.
Ability to work independently and collaboratively in a research team.
English language proficiency (if required by QMUL for non‑native speakers).