Dolby Careers PhD Research Intern Neuroscience + AI (Fall 2026)

Multimodal Experiences Lab - Advanced Technology Group

We are seeking exceptional interns to join ourcutting-edgeresearch at the intersection of physiological measurement computational neuroscience and next-generation media experiences. You will have the opportunity to develop novel approaches to measuring user engagement through cardiovascular dynamics neuralactivity andotherbiosignalanalysis to enable personalized adaptive media content. As an intern you will work closely with our team ofresearchers and scientists to advance the frontier of engagement-aware media systems thatleverageAI and foundation models to adapt in real-time to user state and preferencesderived from physiological data.

What are we looking for in candidates

Along with your solid technical skills candidates shoulddemonstrateproblem-solvingand analytical abilitiesgoodcommunicationandcollaborationskills acuriosityfor how and why things work as they do and apassionfor understanding humanperceptionand engagement with media. You have a desire to bring innew ideasand are open to learning from others and working in a team environment focused on transforming the future of entertainment experiences through AI-driven physiological understanding.

You may succeed in this role if you are a PhD candidate in neuroscience biomedical engineering computer science or related fields and you are excited about bridging physiological measurement with AI and media technology to create more engaging and personalized experiences.

Example Responsibilities

• Work collaboratively with our team to design and implement experiments measuring cardiovascular dynamics (heart rate variability PPG) and autonomic physiology (EDA) during media consumption across different content types and viewing contexts.

• DevelopEEG-basedneural signature models for media componentsand eventscombiningnaturalistic media stimuliwithAI-based content analysis.

• Createbiosignaltransfer learningapproachesthatestablishrobust mappingsbetween high-fidelity neural signatures and accessible physiological measures from consumer wearable devices.

• Build foundation models for physiological data representation that can generalize across individuals devices and measurement contexts to enable scalable engagement prediction systems.

• Implement temporal engagement modelsto predict user state trajectories andoptimizecontent adaptation timing for sustained engagement across diverse media experiences.

• Develop multimodal AI systems that integrate physiological signals content features and contextual information to predict and enhance user engagement in real-time media applications.

• Leverage large-scale physiological datasets to train foundation models that capture universal patterns in human engagement responses while preserving individual personalization capabilities.

• Contribute to the development of research papers patents and technical presentations advancing the field of AI-drivenandengagement-aware media systems.

Requirements

• Currently pursuing aPhD degreein neurosciencecomputational neurosciencebiomedical engineering computer science electrical engineering cognitive science or a related field.

• Strong programming and prototyping skills inPythonMatlab or similar languages with experience in signal processing time-seriesprediction andanalysis and AI/ML frameworks (PyTorch TensorFlow).

• Familiarity withphysiological signal acquisition and analysis particularly cardiac signals (ECG PPG HRV)electrodermal activity(EDA) and EEGmeasurements.

• Experience with machine learning techniques and algorithms particularly deep learning transfer learning and foundation models applicable to physiological data and temporal modeling.

• Understanding of AI model development including data preprocessing feature engineering model training and evaluation forbiosignalapplications.

• Understanding of experimental design hypothesis testing and collection of perceptual and physiological data in controlled settings.

• Analytical skills and the ability to manipulate visualize and extract meaning from complex physiological and behavioral datasets.

• Excellent communication and teamwork skills.

• Ability to work independently and take initiative on complex interdisciplinary problems involving AI and human physiology.

Highly Desirable

• Experience developing foundation models or large-scale representation learning for physiological or biomedical data.

• Prior work with transformer architecturesstate space modelsself-supervised learning or contrastive learning methods applied to time-series physiological data.

• Experience with real-time gaming/simulation engines such as Unity or Unreal for creatingvirtualexperimental environments.

• Knowledge of multimodal AI systems that combine physiological behavioral and content-based signals.

• Prior work with EEG analysis event-related potentials or other neuroimaging techniques combined with AI interpretation methods.

• Understanding of wearable sensor technologies their data characteristics and approaches for handling sensor heterogeneity.

• Experience with edgemeasurement and MLdeploymenttechniquesfor real-time physiological monitoring and engagement prediction.

• Background in human-computer interaction user experience research or media psychology with AI integration.

Benefits

• Gain hands-on experience incutting-edgeresearch combining AI physiological measurement and next-generation media technologies.

• Work alongside experienced engineers researchers and scientists specializing in AI neuroscienceperceptionsciencenetworkdeliveryand media systems.

• Develop skills in experimental design multimodal data collection advanced signal processing and AI/ML applications to human physiology.

• Contribute to research that will shape the future of AI-powered personalized adaptive media experiences.

• Collaborate with teams developingrecomposablemedia platforms content intelligence systems and AI-driven rendering technologies.

If you are passionate about understanding human engagement through physiological measurement and applying these insights to create more compelling media experiences we encourage you to apply for this internship. We welcome applicants from diverse backgrounds and are committed to creating an inclusive and supportive work environment where innovationinhuman-centered technology thrives.

We will review applications on a rolling basis. For the best chance to have your resume reviewed and considered we recommend submittingyour application byJune 26 2026.

Eligibility

Working towards a PhD degree in neuroscience biomedical engineering computer science or related field; recent graduates within six months of graduation are also eligible to apply. Must be available to work full-time Monday to Friday for12 weeks between September - December 2026.

The start date for this internship is as follows (please note these dates are not flexible):

• September 21 2026