Partially Funded PhD Scholarships in the Field of AI at the University of Sussex in the UK
Applicant criteria
- 7 - 60
- Both
Opportunity criteria
Opportunity description
The University of Sussex invites all researchers passionate about AI to Phd scholarships. It is a project with Dr. Ivor Simpson, a lecturer in the Predictive Analytics Lab within the AI research group. This research scholarship will advance the understanding of how to effectively and efficiently produce and use uncertainty estimates on predictions from AI models for downstream medical image analysis and computer vision tasks. The specific application areas for this project are flexible and will be depending on the student’s interest. Some potential topics include:
- Magnetic resonance image analysis.
- Image registration and tracking.
- Segmentation.
- Image-to-image translation and depth estimation.
Benefits
If you get this scholarship, you will have:
- A tax-free stipend at a standard rate of £15,609 per year for 3.5 years.
- Waived from your fees for 3.5 years.
Eligibility criteria
You must have:
- Recently received an MSc and/or a First or high 2:1 BSc in a relevant subject.
- Good mathematical and programming skills.
- A keen interest in probabilistic machine learning and computer vision.
- Students will be expected to present their work at computer vision, medical image analysis, or machine learning venues such as CVPR, ICCV/ECCV, MICCAI, NeurIPS.
- Fluent in the English language.
- This is a full-time scholarship.
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About the University of Sussex:
The University of Sussex is a leading research-intensive university near Brighton. Sussex was the first of the new wave of UK universities founded in the 1960s, receiving its Royal Charter in 1961. This was a historic moment, not just for Sussex, but for higher education in the UK. It has over 14,000 students and more than 2,000 staff members. It has both an international and local outlook, with staff and students from more than 100 countries and frequent engagement in community activities and services.
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