PhD Research Intern; Summer

Join the leader in entertainment innovation and help us design the future. The Dolby U internship program offers impactful, project-based work experience in a collaborative, creative environment where you work side by side with industry leaders. Amplify your insatiable curiosity by implementing real-world solutions that revolutionize how people communicate and how entertainment is created, delivered, and enjoyed worldwide. We offer a collegial culture, challenging projects, and excellent compensation and benefits, not to mention a Flex Work approach that is truly flexible to support where, when, and how you do your best work.

For any student seeking to gain invaluable expertise through meaningful, personal contributions, we invite you to join us in continuing to design a future where technology meets entertainment!

The Advanced Technology Group (ATG) is Dolby's research division, focused on developing next-generation technologies that shape the future of entertainment and media experiences. ATG researchers work across audio, imaging, video, cloud, data, AI/ML, algorithms, signal processing, computer vision, neuroscience, perception science, AR/VR, distributed systems, edge and mobile computing, networking, HCI, and immersive media technologies.

As a Research Intern, you will define and lead a novel research project in collaboration with Dolby researchers. You will contribute to innovations that connect rigorous technical research with real-world media experiences, with the goal of enhancing how people create, deliver, and experience entertainment.

With the guidance of Dolby’s leading media technology experts, you will delve into your own innovative projects across exciting domains, which could include, but not limited to:
Automotive, Smart Glasses, Live Sports, Consumer Devices, Human - Machine Interfaces, and Media Personalization.

• Currently pursuing a PhD in Computer Science, Electrical Engineering, Computer Engineering, Artificial Intelligence, Data Science, Neuroscience, Music Technology, Bioengineering, or a related technical field.
• Strong research background demonstrated through publications, patents, prototypes, projects, demos, or technical reports.
• Experience applying advanced algorithms, machine learning, data science, signal processing, computer vision, or related methods to real-world problems.
• Proficiency in Python, C/C++, MATLAB, or similar programming and research tools.
• Preferred experience with modern AI frameworks such as PyTorch or Tensor Flow, GPU-accelerated computing, multi-GPU clusters, or cloud-based training environments.
• Strong analytical, problem-solving, communication, and collaboration skills.
• Curiosity, openness to learning from others, and interest in bringing new ideas into technical research.
• Passion for advancing technologies that enhance audio, video, media, entertainment, and human experiences.

Experience in one or more of the following areas is highly desirable. Candidates are not expected to have expertise in all areas.

• Machine learning, deep learning, foundation models, large language models, multimodal AI, or generative AI.
• Training, fine-tuning, evaluation, or deployment of AI models for media understanding, enhancement, personalization, content generation, or human interaction.
• Self-supervised learning, contrastive learning, representation learning, explainable AI, trustworthy AI, robustness, uncertainty, or model evaluation.
• Experience with modern AI frameworks such as PyTorch or Tensor Flow, GPU-accelerated computing, multi-GPU clusters, or cloud-based training environments.
• Generative AI:
  Diffusion models, multimodal generation, media synthesis, cont rollability, representation learning, evaluation, or content authenticity.
• Agentic AI Systems:
  Autonomous agents, multi-agent systems, planning, reasoning, tool use, workflow automation, AI systems evaluation, or human-in-the-loop AI.

• Audio signal processing, speech processing, music information retrieval, acoustics, spatial audio, or audio perception.
• Machine learning applied to audio, speech, music, media understanding, source separation, synthesis, enhancement, or rendering problems.
• Real-time audio algorithm implementation, playback and recording systems, acoustic measurement techniques, critical listening, music production, or game-engine audio rendering.

• Computer vision,…