Research Scientist, Machine Learning (PhD)

The role

The researcher will develop new machine learning methods for modeling high-dimensional neural and behavioral data. This involves learning latent structure from noisy time-series data and translating research into real-time systems.

What you will do

• Develop new machine learning methods for modeling high-dimensional neural and behavioral data
• Learn latent structure and dynamics from noisy, non-stationary, partially observed time-series data
• Develop approaches to neural decoding that generalize across people, sessions, tasks, and recording conditions
• Explore problems at the intersection of deep learning, dynamical systems, control, and statistical learning
• Investigate self-supervised and unsupervised learning methods
• Design rigorous experiments to understand model scaling and generalization
• Build simulations and generative models for studying neural signals
• Work closely with researchers and engineers
• Translate promising research into real-time systems
• Build rigorous, reproducible implementations of research ideas

Required qualifications

• PhD or equivalent demonstrated research ability in machine learning, computer science, applied mathematics, physics, statistics, computational neuroscience, electrical engineering, or a related techni
• Evidence of exceptional ability to conduct original research
• Strong mathematical foundations in linear algebra, probability, optimization, statistics, information theory, or dynamical systems
• Strong programming ability and experience implementing and evaluating machine learning models in PyTorch, JAX, or equivalent frameworks
• Experience working with high-dimensional, sequential, scientific, sensory, or otherwise complex datasets
• Ability to take an ambiguous research problem from first principles through formulation, experimentation, analysis, and implementation
• Ability to operate independently, question existing assumptions, and pursue technically ambitious ideas

Nice to have

• Representation learning and self-supervised learning
• Foundation models
• Generative modeling
• Time-series or sequence modeling
• Latent-variable and state-space models
• Dynamical systems and system identification
• Scientific machine learning
• Inverse problems
• Reinforcement learning and optimal control
• Information theory

Benefits

• Competitive salary
• Meaningful & generous equity ownership
• Comprehensive health benefits
• Paid holidays
• Unlimited PTO

About the company

Synaptrix is building non-invasive brain-computer interfaces by treating neural decoding as a fundamental machine learning problem. They are developing new models, datasets, and hardware to translate neural dynamics into real-time control of machines.