AI Research Scientist, Neural Interfaces (PhD) Responsibilities:
- Plan and execute cutting-edge applied research to advance neural interface capabilities.
- Use quantitative research methods to define, iterate upon and advance key areas of our research agenda.
- Collaborate with engineering and HCI teams to translate fundamental scientific knowledge into new technology.
Minimum Qualifications:
- Currently has, or is in the process of obtaining, a PhD in the field of computational neuroscience, machine learning, computer science, electrical engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
- Research-oriented software engineering skills, including fluency with libraries for scientific computing (e.g. SciPy ecosystem) and machine learning (e.g. Scikit-learn, PyTorch, JAX, TensorFlow).
- Proficiency with quantitative methods (mathematics, statistics) and experience learning new technical knowledge and skills rapidly.
- 3+ years of experience working autonomously to design, execute, interpret, and present research studies.
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
- Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
Preferred Qualifications:
- Experience working and communicating cross-functionally in a team environment.
- Experience in signal processing and familiarity with real-time signals.
- Experience with large scale cluster computing for machine learning modelling.
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, COSYNE or similar.
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
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