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

Meta

Menlo Park, CAInternship$7,650–12,667/moSeen 4 days agoSeen in employer's feed 4 days ago

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At a glance

Compensation
$7,650–12,667/mo
Location
Menlo Park, CA
Role Type
Internship
Schedule
Internship
Work Authorization
Not specified

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Requirements

Credentials this posting asks for.

Doctorate

Job overview

Reality Labs at Meta seeks PhD research interns to advance neural interfaces using non-invasive body signals such as EMG, IMU, and PPG. Interns 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 experiences. Internships last 12 to 24 weeks, with start dates throughout the year.

Skills & qualifications

RequiredNice to have

Skills

Scientific PythonPyTorchMachine LearningDeep LearningSignal ProcessingComputer VisionProbabilistic Graphical ModelsNatural Language ProcessingBiosignal ProcessingWearable Sensor DataMulti-Channel Array ProcessingReal-Time Signal ProcessingSequence ModelingDistributed TrainingMulti-GPU TrainingResearch PrototypingSoftware Engineering

Qualifications

PhD in Listed or Related FieldResearch Implementation ExperienceReturn to Degree ProgramIndustry Software Engineering Experience

Full job description

Summary:

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.

Required Skills:

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

  1. 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.

  2. Design methods, tools, and infrastructure to analyze and make use of rich multimodal datasets.

  3. Adapt machine learning methods to modern parallel computing environments (e.g., distributed clusters and GPUs).

  4. Work with engineering and Human-Computer Interaction (HCI) teams to turn research into new technology and user experiences.

  5. Use quantitative research methods to define, iterate on, and advance key areas of our research agenda.

Minimum Qualifications:

Minimum Qualifications:

  1. 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

  2. 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

  3. Experience in machine learning, deep learning, signal processing, computer vision, probabilistic graphical models, and/or natural language processing

  4. Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment

Preferred Qualifications:

Preferred Qualifications:

  1. Intent to return to degree program after the completion of the internship

  2. Experience working with biosignals or wearable sensor data (e.g., EMG, IMU, PPG, EEG)

  3. Experience with multi-channel array processing or real-time signal processing

  4. Experience with sequence modeling of time-series data

  5. Experience training machine learning models at scale, including distributed or multi-GPU training on large datasets

  6. Experience moving machine learning research into prototypes or products

  7. Experience in software engineering in industry, including prior internships

Public Compensation:

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

Industry: Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and Affirmative 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 [email protected].

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