Research Scientist Intern, Multimodal Behavioral Modeling, Hearing Science (PhD)

Meta; Redmond; On-site; AUD 123,000 - 204,000; Full time

Job summary

Meta Reality Labs Research Audio seeks a PhD candidate for a Research Scientist Intern in Multimodal Behavioral Modeling, Hearing Science. You will build ML models from wearable data to infer listening states and validate with hearing science measures.

Ideal candidates have strong Python/ML skills, experience with deep learning (PyTorch), and a background in hearing science or cognitive neuroscience. This internship lasts 12–24 weeks with various start dates.

Qualifications

• PhD in machine learning, computer science, hearing science, or related field.
• 2+ years Python for data analysis and modeling.
• 2+ years of statistical modeling or ML at doctoral level.
• Experience with multimodal behavioral data, speech perception, or conversational communication.
• Must have work authorization in country of employment.

Responsibilities

• Develop ML models inferring listening and communication behavior from multimodal wearable data.
• Relate model outputs to hearing science measures for validation.
• Design data collection strategies, benchmarks, and metrics for limited ground truth.
• Design, run, and analyze human subjects experiments in lab and natural listening environments.
• Collaborate with researchers across hearing science, audio signal processing, ML, and perception science.
• Communicate the research agenda, progress, and analyses of results.

Skills

Python

Machine learning

Multimodal data

Data analysis

Statistical modeling

Research experience

Communication across teams

Education

PhD in ML/CS/Hearing science

Tools

PyTorch

Job description

The Meta Reality Labs Research Team brings together a world-class team of researchers, developers, and engineers to create the future of virtual and augmented reality, which together will become as universal and essential as smartphones and personal computers are today. In particular, the Meta Reality Labs Research Audio team works on technologies that help people hear and communicate better in everyday life, from spatial audio to hearing assistance on AI glasses. Recent work includes Conversation Focus, which helps people hear the person they're talking to in noisy environments. As wearable devices become part of daily life, understanding how people actually listen, attend, and communicate in real‑world settings is central to building audio experiences that adapt to each person.We are looking for interns who want to model how people listen and communicate in the real world. Using multimodal, egocentric data from wearable devices (eye and head movement, speech and vocal behavior, gesture, and the acoustic scene), the intern will build models that infer listening and communication states such as auditory attention, listening effort, and conversational engagement. Ground truth for these states is often sparse or ambiguous. The goal is to inform hearing assistance and audio technologies that adapt to the listener.The role suits candidates with a background in machine learning, computer science, hearing science, or auditory or cognitive neuroscience, who want to work at the intersection of those fields. Successful candidates will combine strong quantitative and machine learning skills with an understanding of human hearing and communication. Specific projects will be designed with successful applicants to match their skills and experience to current research needs. Our internships are twelve (12) to twenty‑four (24) weeks long and we have various start dates throughout the year.

Research Scientist Intern, Multimodal Behavioral Modeling, Hearing Science (PhD) Responsibilities:

• Develop novel machine learning and statistical models that infer listening and communication behavior from multimodal wearable data (for example gaze, head movement, vocal cues, and turn‑taking dynamics), with applications to hearing assistance.
• Relate model outputs to established hearing science measures, such as speech intelligibility, listening effort, and self‑reported communication difficulty, to validate what the models capture.
• Design data collection strategies, benchmarks, and metrics for models trained on limited or ambiguous ground truth, including data from listeners with and without hearing loss.
• Design, run, and analyze human subjects experiments in laboratory and naturalistic listening environments.
• Collaborate with researchers and engineers across hearing science, audio signal processing, machine learning, and perception science.
• Communicate the research agenda, progress, and full analyses of results.

Minimum Qualifications:

• Currently has, or is in the process of obtaining, a PhD in machine learning, computer science, hearing science, or auditory or cognitive neuroscience, or a related field
• 2+ years of experience with Python or a similar language for data analysis and modeling
• 2+ years of experience in statistical modeling and/or machine learning at the doctoral level, including time‑series or sequential data
• Research experience with one or more of the following: multimodal behavioral data (e.g., eye tracking, motion, physiological, or speech signals), speech perception, auditory attention, or conversational communication
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Preferred Qualifications:

• Proven track record of results as demonstrated by grants, fellowships, patents, or first‑authored publications at venues such as ARO, ASA/JASA, Ear and Hearing, Trends in Hearing, JSLHR, ICASSP, Interspeech, ICMI, ETRA, CHI, NeurIPS, or similar
• Experience with deep learning frameworks such as PyTorch, including multimodal or sequence models
• Experience with data from wearable or egocentric sensors (e.g., eye tracking, IMU, head‑worn microphones), especially in naturalistic or conversational settings
• Experience with hearing‑impaired populations, hearing aids, or cochlear implants
• Experience modeling under limited data, weak labels, or ambiguous ground truth
• Experience working with large, high‑dimensional datasets from multiple sources
• Experience working and communicating cross‑functionally in a team environment
• Intent to return to a degree program after the completion of the internship/co‑op

About Meta:

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

Meta is proud to be an Equal Employment Opportunity and Affinity Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E‑Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [e-mail].

$7,650/month to $12,667/month + benefits

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.