Research Scientist Intern, Neuro-AI - Brain & AI Team (PhD)
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Key details
Why this role is notable
Meta is recruiting neuroscientists and computational neuroscience PhDs to a dedicated Brain & AI team, signaling that it is treating brain-inspired algorithms as a serious research bet rather than a fringe academic interest.
Job Description
We are committed to advancing the intersection of neuroscience and artificial intelligence by making fundamental advances in technologies that bridge our understanding of biological and artificial intelligence. The Brain & AI team is seeking individuals passionate about neuro-AI, including areas such as computational neuroscience, neural coding, brain-inspired machine learning, neural network interpretability, and cognitive modeling. Our interns have an opportunity to make core algorithmic advances at the frontier of neuroscience and AI, and apply their ideas at scale. Our internships are up to six (6) months long and we have various start dates throughout the year.
Responsibilities
Develop novel neuro-AI algorithms that draw inspiration from neuroscience to advance machine learning techniques Investigate neural representations and dynamics to inform the design of brain-inspired AI systems Perform state-of-the-art research advancing the science of Neuro-AI, bridging computational neuroscience and artificial intelligence Analyze neural data and develop computational models to understand brain function and translate insights to AI Collaborate with researchers in neuroscience and AI, as well as cross-functional partners, communicating research plans, progress, and results Contribute to research that can be applied to Meta product development
Qualifications
Currently has or is in the process of obtaining a Master's or PhD degree in Neuroscience, Computational Neuroscience, Machine Learning, Artificial Intelligence, Computer Science, Cognitive Science, or relevant technical field Must obtain work authorization in France at the time of hire and maintain ongoing work authorization during employment Experience with Python Experience with deep learning frameworks such as PyTorch or TensorFlow Experience building systems based on machine learning and/or deep learning methods Research experience at the intersection of neuroscience and AI, including computational modeling of neural systems or brain-inspired algorithms Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub) 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, ICLR, ICML, Cosyne, CCN, SfN, or similar Demonstrated experience and experience in solving analytical problems using quantitative approaches Experience working and communicating cross-functionally in a team environment Research experience in computational neuroscience, neural data analysis, brain-computer interfaces, or cognitive modeling Intent to return to degree program after the completion of the internship Experience with neural recording analysis techniques (e.g., electrophysiology, fMRI, or similar)
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Core fields
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