Internship - Reconstruction/Novel View Synthesis of Dynamic Scenes

Job description

MERL is looking for a highly motivated intern to work on an original research project in reconstruction/rendering dynamic 3D scenes. A strong background in 3D computer vision and/or computer graphics is required. Experience in the latest advances of deep learning in this area, such as neural radiance fields (NeRFs)/Gaussian Splatting (GS)/Point Map reconstruction methods, is an added plus and will be valued. The successful candidate is expected to have published at least one paper in a top-tier computer vision/graphics or machine learning venue, such as CVPR, ECCV, ICCV, SIGGRAPH, 3DV, ICML, ICLR, NeurIPS or AAAI, and possess solid programming skills in Python and popular deep learning frameworks like Pytorch. The goal would be for such a candidate to collaborate with MERL researchers to develop algorithms and prepare manuscripts for scientific publications. The position is available for graduate students on a Ph.D. track or those that have recently graduated with a Ph.D. Duration and start dates are flexible but are expected to last for at least 3 months. This internship is preferred to be onsite at MERL’s office in Cambridge, MA. Required Specific Experience: The pay range for th...