Research Scientist Intern, AI-Driven Neural Interfaces (PhD)

Meta; Menlo Park (CA); On-site; USD 55,000 - 83,000; Part time

Job summary

Reality Labs at Meta seeks PhD research interns to push neural interfaces using non-invasive signals like EMG, IMU, and PPG. You will join a world-class team to develop ML methods, analyze multimodal datasets, and adapt models for modern GPUs, with multiple start dates throughout the year.

This twelve- to twenty-four-week internship in Menlo Park, CA offers hands-on research experience across ML, signal processing, and HCI, enabling contributions to AR/VR interaction tech.

Qualifications

• PhD required or in progress in ML, computational neuroscience, signal processing, CS, statistics, physics or related field.
• Fluent in scientific Python and PyTorch with research experience or open-source contributions.
• Experience in ML, DL, signal processing, CV, probabilistic models or NLP.
• Must have work authorization in the country of employment and intent to return to degree program after internship.
• Experience with biosignals or wearable sensor data (EMG, IMU, PPG, EEG) and sequence modeling.
• Experience training ML models at scale (distributed/multi-GPU).
• Experience moving ML research into prototypes or products.

Responsibilities

• Research and develop neural networks, ML, or computational models using EMG, IMU, and sensor data to advance neural interfaces.
• Design tools and infrastructure to analyze multimodal datasets.
• Adapt ML methods to distributed clusters and GPUs.
• Collaborate with engineering and HCI teams to turn research into new tech and experiences.
• Use quantitative methods to define and advance research agenda.

Skills

Python (scientific)

Deep learning

Signal processing

Machine learning

Time-series modeling

Distributed / multi-GPU training

Research & written communication

Education

PhD in machine learning, computational neuroscience, signal processing, CS, or related field

Tools

PyTorch

Job description

About

Reality Labs at Meta is looking for PhD research interns to advance our pioneering work in neural interfaces, which grew out of the acquisition of CTRL-labs. We're building a practical interface that draws on rich signals measured non-invasively from the body, including surface electromyography (EMG), inertial measurement units (IMU), and photoplethysmography (PPG). This technology could become one of the main pillars for interaction with virtual and augmented realities. Help us unleash human potential by removing the bottlenecks between user intent and action.In this role you will join a world-class, multi-disciplinary team of researchers. You'll investigate the nature of human neuromotor and other sensor signals, develop new signal processing and machine learning methods to infer a user's intent, and help create AI-first new interaction techniques and user experiences. Our internships are twelve (12) to twenty-four (24) weeks long, and we have various start dates throughout the year.

Responsibilities

• Research and develop neural networks, machine learning, or other computational models that use EMG, IMU and other relevant sensor data to advance neural interface capabilities.
• Design methods, tools, and infrastructure to analyze and make use of rich multimodal datasets.
• Adapt machine learning methods to modern parallel computing environments (e.g., distributed clusters and GPUs).
• Work with engineering and Human-Computer Interaction (HCI) teams to turn research into new technology and user experiences.
• Use quantitative research methods to define, iterate on, and advance key areas of our research agenda.

Minimum Qualifications

• Currently has, or is in the process of obtaining, a PhD in machine learning, computational neuroscience, speech and language technologies, signal processing, electrical engineering, computer science, statistics, physics, or a related field
• Research-oriented implementation skills, including fluency in scientific Python and deep learning frameworks such as PyTorch, as shown by academic or professional research experience or contributions to open source projects
• Experience in machine learning, deep learning, signal processing, computer vision, probabilistic graphical models, and/or natural language processing
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment Intent to return to degree program after the completion of the internship
• Experience working with biosignals or wearable sensor data (e.g., EMG, IMU, PPG, EEG)
• Experience with multi-channel array processing or real-time signal processing
• Experience with sequence modeling of time-series data
• Experience training machine learning models at scale, including distributed or multi-GPU training on large datasets
• Experience moving machine learning research into prototypes or products
• Experience in software engineering in industry, including prior internships