Up to 30% off — ends 2 Aug
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Up to 30% off — ends 2 Aug
ONLY00h00m00s
Atlantic Technological University - Sligo
4 months ago
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PhD in Disruptive Technology for SensABLATE: AI-Driven Optical Imaging for Lung Cancer Therapy Atlantic Technological University, Sligo in Ireland
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
Expired
Country
Ireland
University
Atlantic Technological University - Sligo

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About this position
Atlantic Technological University’s Clinical Photonics Group at ATU Sligo is offering a fully funded PhD position within the SensABLATE programme, a flagship research initiative funded by the Disruptive Technologies Innovation Fund (DTIF). SensABLATE unites academic, clinical, and industry partners to develop next-generation precision imaging technologies for lung cancer therapy. The project’s goal is to deliver a transformative intraoperative decision-support platform by integrating advanced optical imaging with artificial intelligence, enabling real-time tissue viability assessment and therapy guidance.
Through SensABLATE, ATU aims to advance translational biophotonics and intelligent imaging platforms toward clinical deployment, reinforcing Ireland’s leadership in medical device innovation. The successful candidate will join a multidisciplinary team working at the intersection of AI, biomedical engineering, and medical physics, with a focus on developing and applying machine learning and image analysis techniques to biomedical optics and hyperspectral imaging.
The position is fully funded for three years, with a stipend of €22,000 per annum, tuition fees covered up to €5750 per annum, and a consumable budget included. Funding is provided by Atlantic Technological University and Enterprise Ireland. The project is based at ATU Sligo, with a tentative start date of May 1, 2026.
Applicants should have a Level 8 Honours degree (First or Second Class) or a Master’s degree in AI, Data Science, Biomedical Engineering, Physics, Computer Science, or a related discipline. Essential skills include strong programming ability in Python, with experience in PyTorch and/or TensorFlow desirable. A background in machine learning and image analysis is required, and interest or experience in biomedical optics, hyperspectral imaging, or medical imaging is advantageous. Knowledge of real-time systems, embedded processing, or computational optimisation is also desirable. Non-native English speakers must provide current evidence of English proficiency (IELTS Academic 6.0 overall, minimum 5.5 in each component, or recognised equivalent).
To apply, submit your CV (including contact details of two referees), transcript of results, and a personal statement (max 1 page) outlining your qualifications, experience, and motivation for this PhD as a single Word or PDF file by email to Dr. Karina Litvinova at [email protected]. The application deadline is March 23, 2026.
For more information, visit the project page.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
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