ATU
PhD-Disruptive Technology-SensABLATE
✓ Fully Funded
⏰ Closing Soon
🎓 Artificial Intelligence
🎓 Biomedical Engineering
🎓 Data Science
🎓 Medical Physics
🎓 Optical Physics
deep learning
AI healthcare
biophotonics
clinical AI
hyperspectral imaging
image analysis
lung cancer
medical imaging
real-time systems
Fully funded PhD in Ireland under the SensABLATE programme, combining AI and optical imaging for real-time cancer surgery support. Focuses on intelligent imaging systems for lung cancer diagnosis and treatment guidance.
Project Description
This PhD is part of the SensABLATE programme, a major collaborative initiative led by Atlantic Technological University and funded under Ireland’s Disruptive Technologies Innovation Fund.
The project focuses on developing next-generation medical imaging systems that combine advanced optical techniques with artificial intelligence to support real-time clinical decision-making during lung cancer surgery.
By integrating hyperspectral imaging and machine learning, the research aims to create an intelligent intraoperative platform capable of assessing tissue viability and guiding therapy with high precision.
Key objectives include:
Developing AI models for real-time image analysis
Integrating optical imaging with intelligent decision-support systems
Enhancing accuracy in detecting cancerous vs healthy tissue
Supporting clinical deployment of next-generation imaging technologies
The project sits at the intersection of AI, biomedical engineering, and photonics, with strong translational potential in healthcare and medical device innovation.
Entry Requirements
Honours degree (2:1 or above) or Master’s in AI, Data Science, Biomedical Engineering, Physics, Computer Science, or related field
Strong programming skills in Python
Experience with machine learning and image processing
Familiarity with PyTorch or TensorFlow (desirable)
Interest in biomedical imaging or healthcare applications
English proficiency (IELTS 6.0 or equivalent, if required)
Strong programming skills in Python
Experience with machine learning and image processing
Familiarity with PyTorch or TensorFlow (desirable)
Interest in biomedical imaging or healthcare applications
English proficiency (IELTS 6.0 or equivalent, if required)
How to Apply
Apply by email directly to the supervisor:
karina.litvinova@atu.ie
Submit:
CV (including two referees)
Academic transcripts
Personal statement (max 1 page covering motivation and background)
All documents must be combined into a single PDF or Word file.
karina.litvinova@atu.ie
Submit:
CV (including two referees)
Academic transcripts
Personal statement (max 1 page covering motivation and background)
All documents must be combined into a single PDF or Word file.
Eligibility
UK/Home
EU
International
Supervisor Profile
KL
Karina Litvinova
Atlantic Technological University, Research (Clinical Photonics Group, ATU Sligo)
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