Research Scientist Intern - Graphics, ML

Requirements

• Currently pursuing a PhD in Computer Science, Electrical Engineering, or a related field with a focus on computer graphics and machine learning.
• At least 1 year of academic, research, or industry experience in: - Modern C/C++ and Python programming. - Machine learning concepts, algorithms, and frameworks such as PyTorch. - Advanced graphics techniques including rasterization, ray tracing, physically based rendering, light transport, sampling strategies, acceleration structures, level of detail, shading, appearance modeling, and Monte Carlo methods. - Graphics APIs such as OpenGL, Vulkan, or DirectX, and/or shading languages including GLSL and HLSL. - GPGPU programming technologies such as CUDA, SYCL, or OpenCL.
• Preferred Qualifications Publications in top-tier computer graphics, computer vision conferences, or journals.
• Strong foundation in linear algebra, numerical optimization, probability, and statistical estimation.
• Experience with image processing and computer vision techniques, including multi-scale filtering, Fourier transforms, optical flow, feature alignment, and image segmentation.
• Familiarity with vision transformer models such as DINO, CLIP, and V-JEPA.
• Experience developing neural rendering applications, including super-resolution, denoising, and deblurring.
• Research or software engineering experience through internships, industry roles, open-source contributions, or competitive programming.
• Experience applying machine learning techniques to real-time graphics problems.
• Understanding of GPU architectures, graphics workloads, and performance optimization.
• Experience with profiling, debugging, and performance analysis tools.
• This internship is ideal for PhD students who want to push the boundaries of graphics and AI research while contributing to technologies that impact millions of users worldwide.