48-month full-time PhD Robotic Vision (relocation to Dubai required). Part of the new Centre for Doctoral Training in Robotics and AI, aligned with the UAE's National AI Strategy 2031. Built on the success of the Edinburgh Centre for Robotics, which has graduated 150+ PhDs. Funded: applicants compete for sponsorship (CDT-ECD-SfM-CZ-2025). Research focus: an advanced Structure-from-Motion (SfM) pipeline that harnesses artificial intelligence to enhance feature extraction, matching, and the speed of large-scale 3D reconstruction. Specialisations: Computer Vision and image processing, Deep learning architectures, 3D reconstruction technology, Applications in robotics, AR/VR, digital twins, and asset management. Expected deliverables: AI-enhanced SfM pipeline with advanced feature detection and matching, performance benchmarking against existing solutions, large-scale data processing and optimisation tools, automated quality-control systems, real-world demonstrations for digital twins and asset management, academic publications and open-source software releases. Entry: Master's degree (or equivalent) in Computer Science, Engineering, or related fields; first-class undergraduate degree minimum; strong foundation in linear algebra, calculus, probability, and optimisation. Technical skills: Python proficiency, ML fundamentals (neural networks, supervised/unsupervised learning), computer vision basics and 3D vision concepts, Git, Linux/Unix. Background in Robotics and Computer Vision highly recommended. IELTS 6.5 (no band below 6.0); pre-sessional English available. Application requires: CV, transcripts and certificates (English translation), passport copy, motivation letter, 2 reference letters, English proficiency evidence. Selection: Round 1 technical interview (1 hour incl. 10-min presentation + rapid-fire technical Q&A on maths/CV/ML/coding); Round 2 external supervisor meeting at Expo City Dubai. Tuition AED 103,480/year full-time (incl. VAT).
Duration
4 years
Qualification
PhD
Subject Area
Computer Science
Study Pattern
Full time
Delivery Format
In person