Research Scientist Intern - Graphics, ML

The Graphics Research Organization at Intel is seeking a highly motivated Research Scientist Intern to join its world-class team. This role offers an opportunity to help shape next-generation graphics technologies and experiences by conducting cutting-edge research in real-time 3D rendering, machine learning, and highly parallel algorithms. 

As an intern, you will collaborate with industry-leading researchers to develop innovative graphics and AI techniques. Your work may contribute directly to Intel's graphics hardware and software products while advancing the state of the art in both industry and academia through research publications. 

We are looking for curious, collaborative, and technically strong candidates who are passionate about graphics research, possess excellent communication skills, and are eager to explore new ideas that drive innovation.

• 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. 

• 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. 

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