During the last few decades computer graphics firmly established itself as a core discipline within computer science. New and emerging technologies such as digital media, social networks, digital television, digital photography and the rapid development of new sensing devices, telecommunication and telepresence, virtual and augmented reality further indicate its potential and pose new challenges in the years to come.
To address these challenges, and in particular to seamlessly blend real and synthetic footage, we have adopted a new and more integrated scientific view of computer graphics as 3D Image Analysis and Synthesis that takes into account the whole image processing pipeline from scene acquisition to scene reconstruction to scene editing to scene rendering. We also take into account human perception on all levels of the pipeline, and we exploit the abundance of digital visual data and novel concepts from machine learning to extract powerful priors that can assist us during the acquisition, reconstruction, editing, and image formation processes.
Our vision and long term goal are completely immersive, interactive, and visually rich environments with sophisticated scene representations and the highest visual quality, fused seamlessly with the real world. Standard 2D screens are being replaced with high dynamic range displays, stereo and automultiscopic screens, portable and wearable displays. Imaging algorithms with embedded perceptual models ensure that the perceived quality and viewing comfort is maximized. Interaction is intuitive and light weight.
We are looking for motivated researchers to start as PhD candidates in the Computation, Appearance and Manufacturing Group. The candidates will research the exiting and rising field of computational fabrication. The group has a particular focus on appearance manufacturing using a wide range of advanced manufacturing devices, among which 3D printers. Appearance manufacturing concerns the fabrication of objects with a given appearance and has a variety of applications from medical devices and cultural heritage preservation to stop-motion animation. We have a keen interest in using deep learning methods in the context of manufacturing, where we have taken successful initial steps.
Strong applicants with a master degree (or those approaching the end of their master studies) in computer science or a related field are encouraged to apply. Research background in one or more of the following areas is necessary: computer graphics (with a preference for rendering), geometry processing, image processing or machine learning. Solid skills in mathematics and related programming languages (C++ / Python / OpenGL) are also required.
Please send your application or any inquiry to Dr. Vahid Babaei (email@example.com). The application should include a CV, motivation letter and copy of transcripts. Names of two references agreed to write a recommendation letter are also required.