Join the leader in entertainment innovation and help us design the future. At Dolby, science meets art, and high tech means more than computer code. As a member of the Dolby team, you’ll see and hear the results of your work everywhere, from movie theaters to smartphones. We continue to revolutionize how people create, deliver, and enjoy entertainment worldwide. To do that, we need the absolute best talent. We’re big enough to give you all the resources you need, and small enough so you can make a real difference and earn recognition for your work. We offer a collegial culture, challenging projects, and excellent compensation and benefits.
Advanced Technology Group (ATG) is the research and technology arm of Dolby Labs. It has multiple competencies that innovate technologies in audio, video, AR/VR, gaming, music, and movies. Many areas of expertise related to computer science and electrical engineering, such as AI/ML, computer vision, image processing, algorithms, digital signal processing, audio engineering, data science & analytics, distributed systems, cloud, edge & mobile computing, natural language processing, knowledge engineering and management, social network analysis, computer graphics, image & signal compression, computer networking, IoT are highly relevant to our research.
ATG Bangalore is a fast-growing R&D operation focusing on the next generation of sound, sight, and multi-modal experiences using perceptual sciences, foundational systems, and AI. In this internship you will spend three months with our researchers to investigate a cutting-edge topic. We will work with you to define the problem statement and research plan that leverages your competencies and results in top-tier novel research that is fun and exciting.
We are accepting applications for our Summer 2026 internship cohort (May-Jul 2026) for research in following areas:
Understanding of generative models based on Diffusion Transformers (DiT), UNets, Flow Matching, DDPM
Training and evaluation of audio VAE, audio codecs, audio tokenization, self-supervised audio models
Spatial audio understanding, ambisonics, head related transfer functions (HRTFs), binaural audio simulation/rendering
Speech recognition, speaker diarization, speaker ID, contrastive speech-text, image-text training (CLIP, CLAP), voice activity detection, audio source separation, text to speech, speech to speech translation
Multi-channel audio processing, neural beam-forming, spatial audio event detection and localization
Video processing and training relevant models like video captioning, key frame retrieval
Skills and specialty areas:
PhD candidates in Computer Science, Electrical Engineering, Electrical Communications Engineering, and relevant fields.
Top tier publications is a big plus (e.g. CVPR, ICML, ICCV, ECCV, ICIP, WACV, ACL, ACM, AAAI, ICASSP, T-Pami, IJCNN, JMLR, BMVC, EMVC, INTERSPEECH, NeurIPS, ICLR, ICML, CHI, SIGGRAPH etc)