Research Scientist Intern - Artificial Intelligence-Driven Neural Interfaces

Reality Labs at Meta is looking for PhD research interns to advance its work in neural interfaces, which grew out of the acquisition of CTRL-labs. The team is 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 unleash human potential by removing the bottlenecks between user intent and action. In this role, you will join a multidisciplinary team of researchers. You will investigate human neuromotor and other sensor signals, develop signal processing and machine learning methods to infer user intent, and help create AI-first interaction techniques and user experiences. Internships are twelve to twenty-four weeks long, with 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, such as 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 the 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, demonstrated through academic or professional research experience or open-source contributions. - 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. ## Preferred Qualifications - Intent to return to a degree program after completing the internship. - Experience working with biosignals or wearable sensor data, such as EMG, IMU, PPG, or 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. - Industry software engineering experience, including prior internships.United States compensation: $7,650/month to $12,667/month, plus benefits. Individual compensation is determined by skills, qualifications, experience, and location. The listed compensation reflects base compensation only and does not include bonus, equity, or sales incentives, if applicable.