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

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.

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