Research Scientist Intern, Machine Learning, Health Tech (Phd)

Summary
The Health Technologies team of the Reality Labs is looking for a research intern to help us develop the next generation Machine Learning models that aim to improve the public health outcomes, at Meta scale. We are seeking candidates who have experience with the following domains: Machine Learning for biomedical engineering, natural language processing, computer vision, multimodal learning, self-supervised learning.
Required Skills
Research Scientist Intern, Machine Learning, Health Tech (PhD) Responsibilities:

• Plan and execute cutting-edge research on developing novel Machine Learning models that can benefit public health.
• Conduct SOTA research while collaborating with other researchers, and engineers to develop, prototype, and test different AI/ML models at-scale for real-world health applications. Present and share results with key stakeholders.
• Troubleshoot, debug and upgrade existing models, contribute to code documentation and maintenance of the data pipeline.

Minimum Qualification
Minimum Qualifications:

• Currently has, or is in the process of obtaining, a PhD in computer science, electrical engineering, Machine Learning, biomedical engineering, or related fields.
• 2+ years of experience with Python and in using deep learning libraries and related frameworks, such as Pytorch, TensorFlow, numpy, pandas, scikit-learn.
• Interpersonal skills: cross-group collaboration and cross-culture collaboration. Be able to clearly articulate ideas and goals.
• Excellent research skills involving defining problems, exploring solutions, and analyzing and presenting results.
• Deep understanding of at least one of the following areas: Machine Learning for biomedical engineering, natural language processing, computer vision, multimodal learning, self-supervised learning.
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.

Preferred Qualification
Preferred Qualifications:

• First author publication in a top conference or journal.
• Proven track record in the design of novel and fieldable Machine Learning models for health related applications.
• Experience on working with time sequence form sensor data, such as PPG, CKG, IMU and audio.
• Intent to return to the degree-program after the completion of the internship/co-op.

EOE
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 accommodations-ext@fb.com.