Research Scientist, Neural Interfaces - Machine Learning

Meta; London; On-site; GBP 125,000 - 150,000; Full time

Job summary

A leading tech company in London is seeking an AI Research Scientist to develop machine learning models for neural interfaces. The position requires a PhD in computational neuroscience or a relevant field, along with 3+ years of research experience. The ideal candidate will possess strong software engineering skills and proficiency in various machine learning libraries. This role offers the opportunity to shape the future of non-invasive technology.

Qualifications

• PhD must be completed prior to joining.
• Experience with machine learning libraries required.
• 3+ years of independent research experience.

Responsibilities

• Develop machine learning models for neural interfaces.
• Build machine learning and signal processing models.
• Define and iterate on research methodologies.

Skills

Research-oriented software engineering skills

Proficiency with quantitative methods

Fluency with libraries for scientific computing

Machine learning expertise

Communication skills

Education

PhD in computational neuroscience or related field

Bachelor's degree in Computer Science or related field

Tools

SciPy ecosystem

PyTorch

TensorFlow

Job description

Overview

Reality Labs is seeking an AI Research Scientist to help us unleash human potential by eliminating the bottlenecks between intent and action. To achieve this, we’re building a practical neural interface drawing on the rich motor neuron signals that can be measured non-invasively with neuron-level resolution. Our research lies at the intersection of computational neuroscience, machine learning, signal processing, statistics, biophysics, motor learning, perceptual psychophysics, and human-computer interaction. We’re looking for people who want to shape the future of this technology and leverage state-of-the-art ML to push the limits of non-invasive neuromotor interfaces.

Responsibilities

• Research and develop machine learning models that leverage biosignals to advance neural interface capabilities
• Build cutting-edge machine learning and signal processing models (event detection, sequence-to-sequence, signal separation, time series regression, data compression, data augmentation etc.)
• Use quantitative research methods to define, iterate upon and advance key areas of our research agenda

Minimum Qualifications

• Obtained 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)

Industry: Internet