Research Intern

About the Role

The Interactive Multimodal Futures (IMF) group at Microsoft Research is seeking a PhD-level Research Intern. This role focuses on projects at the intersection of situated interaction, social computing, ubiquitous computing, and human-centered Artificial Intelligence (AI) systems. The project will involve multimodal sensing, signal processing, and real-time interaction.

Group Research Areas

• Human-centered AI for affective and social computing, and adaptive experiences.
• Situated interaction between humans and AI systems, such as robots in the physical world.
• Conversational AI Agents that are socially and context aware.
• Ubiquitous sensing and ambient intelligence with unobtrusive sensing in the real world.

Key Responsibilities

• Design and implement research prototypes for real-time situated and adaptive interaction.
• Explore the use of the latest generative AI techniques for interpreting multimodal interaction, conversation, and behavioral signals.
• Conduct user studies and analyze multimodal data.
• Contribute to publications and share findings with the research community.
• Collaborate with IMF researchers to prototype systems, run user studies, develop machine learning models, and explore technical capabilities of generative AI for human-AI interaction.
• Present findings and contribute to the research community.

Requirements & Tech Stack

• Currently enrolled in a Doctorate degree program in Human-Computer Interaction (HCI), Human-Robot Interaction (HRI), Computer Science, Cognitive Science, Robotics, Electrical Engineering, Psychology, or related STEM field.
• Research Interns are expected to be physically located in their manager’s Microsoft worksite location for the duration of their internship.
• Please include a cover letter indicating your research interests and alignment with preferred qualifications.

Qualifications

• Preferred Qualifications (Address in cover letter):

• 2+ years of research experience using human-centered approaches in HCI, HRI, Machine Learning (ML), Computer Vision (CV), Ubiquitous Computing, or Affective Computing.

• Experience writing peer-reviewed publications.

• Experience with generative AI techniques, ML frameworks (e.g., PyTorch), and real-time interactive systems.

• Proficient collaboration and communication skills.

• Conducting human-subjects research.

• Experience implementing research prototypes (frontend, backend, or both).

• Using human-centered design & research methods.

• Familiarity with reinforcement learning or time-series signal processing.

• Working with large datasets (e.g., text, vision, physiology, behavioral).

• Affective And Social Computing Sub-area:

• Background in affective computing, behavioral, or physiological sensing.

• Experience collecting data with wearable devices.

• Hardware prototyping or wearable device experience.

• Healthcare/wellbeing experience (e.g., pain assessment, stress/anxiety detection).

• Olfaction & gas sensing experience (e.g., electronic noses, breath analysis).

• Situated Interaction Sub-area:

• Demonstrated experience programming multimodal systems interacting with human users, integrating multiple machine-learned components (e.g., computer vision, speech recognition, dialogue handling).

• Demonstrated experience conducting research outside of a controlled lab environment (e.g., field research, ethnography).

• Conversational AI Agents Sub-area:

• Experience prototyping real-time conversational AI agents using tools such as the OpenAI Realtime API.

• Experience designing, implementing, and evaluating different personality styles for AI agents.

• Incorporating multimodal sensory inputs to enhance interaction quality.

• Ubiquitous Computing And Ambient Intelligence Sub-area:

• Leveraging AI techniques for real-world sensing.

• Working with multimodal AI models.