Neuroscience ML Research Intern — 1 Year (Hybrid)

Allen Institute; Seattle (WA); Hybrid; USD 43,000 - 62,000; Part time

Job summary

Allen Institute invites a Research Intern – Machine Learning for Neuroscience to work on large-scale neural and behavioral datasets. The one-year, part-time position blends machine learning with neuroscience and is mentored directly.

The intern will develop models to understand coordination across neural populations and will have potential conference or manuscript contributions. Starting late fall 2026, the role supports a hybrid work setup in Washington state, with on-site presence required at

Qualifications

• Currently enrolled in a master’s or PhD program in a quantitative field.
• Completed coursework in programming, linear algebra, probability and statistics, and ML or signal processing.
• Demonstrated experience with scientific computing in Python (numpy, scipy, pandas).
• Available to start in late October / early November 2026 and able to commit to the position for one year.
• Able to work onsite at least one day per week.

Responsibilities

• Characterize coordinated neural population activity to encode forelimb force.
• Implement and evaluate ML and latent variable models for shared vs population-specific covariance.
• Relate neural activity to behavior using regression and classification with cross-validation.
• Extend analysis to EMG and video data; study learning across days.
• Produce documented Python analysis code for the team; version-controlled.
• Communicate results to scientists and contribute to posters and manuscripts.

Skills

Strong written communication

Verbal communication

Independent work

Collaborative work

Education

Master’s or PhD in ECE / CS / quantitative field

Tools

Python

NumPy

SciPy

Pandas

scikit-learn

PyTorch

DeepLabCut

SLEAP

Lightning Pose

Job description

Allen Institute invites a Research Intern – Machine Learning for Neuroscience to work on large-scale neural and behavioral datasets. The one-year, part-time position blends machine learning with neuroscience and is mentored directly.

The intern will develop models to understand coordination across neural populations and will have potential conference or manuscript contributions. Starting late fall 2026, the role supports a hybrid work setup in Washington state, with on-site presence required at