- Play a leading role in establishing and delivering the research project.
- Undertake a broad range of research related to the major goals of the project.
- Write up results for publication in conferences or journals.
- PhD in Computer Vision or a related AI subject is required.
- Previous experience of research in a relevant discipline (computer vision, 3D reconstruction, facial models, deep learning).
- Previous major contribution to at least one paper in a peer-reviewed publication is required.
- Ability to work independently with minimal supervision while operating as part of a team.
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Post-Doctoral Research Assistant - Dundee, United Kingdom - University of Dundee
Description
The School of Science and Engineering has an international reputation for excellent teaching and research, particularly in addressing global challenges in environment, health care, technology, forensic science and infrastructure.
With its award winning Centre for Anatomy and Human Identification, and departments in engineering, computing, physics and mathematics, the School offers state of the art facilities which prepare and inform the scientists and engineers of tomorrow. The School is one of the fastest growing within the University and run by enthusiastic, committed and approachable experts recognised for their teaching approaches.
We are looking for an exceptional candidate to join our team in the project within the Computer Vision and Image Processing research group. The project is a collaboration between the University of Dundee and University of Glasgow which aims to develop and test a system to obtain highly accurate and dense facial 3D reconstruction from end users mobile devices in real world conditions.
The successful candidates will work on AI and Computer Vision algorithms to design and implement a facial 3D reconstruction method adapted to dysmorphology from multiples images acquired using a mobile application by the user themselves. This research work will include exploring the use of multi-view geometry constraints and facial features in image synthesis based 3D reconstruction to guide the learning rather than statistical models such as 3DMM currently used in most facial 3D reconstruction methods. Collection of a new dataset containing examples of dysmorphology and real world condition of use will also be carried out to assess the performance of the developed system.
Your priorities will include:
Who we're looking for:
We are one of the UK's leading universities, internationally recognised for our expertise across a range of disciplines and research breakthroughs in multiple areas, including science, medicine and engineering, amongst many others. Our purpose is to transform lives, locally and globally, which we do as a community of staff, students and alumni.
For further information about this position please contact: Ludovic Magerand