Postdoc: Computational Neuroscience for Epilepsy

Mass General Brigham; Boston (MA); On-site; USD 72,000 - 81,000; Full time

Job summary

Mass General Brigham in Boston is seeking a Research Fellow (Postdoctoral) to advance NIH-funded neural dynamics research using large RNS datasets from Brigham and Women’s and Massachusetts General Hospitals. The role centers on turning ECoG data into quantitative brain-state measures and building predictive models of seizure outcomes.

The ideal candidate has a PhD in a quantitative field or an MD with quantitative training, strong coding in Python/MATLAB/Julia, and a track record of

Qualifications

• PhD in a quantitative field or MD with quantitative training.
• Strong programming in Python, MATLAB or Julia.
• Depth in signal processing, statistical modeling or machine learning.
• At least one first-author paper or preprint.
• Preferred: time-series or causal methods, neuroimaging analysis, or experience with neural data.

Responsibilities

• Turn long-term ECoG and device time series into quantitative measures of brain state.
• Use statistics and machine learning to link electrode location, stimulation timing, and brain rhythms to seizure outcomes.
• Build prediction models and validate them in prospective patients and at other centers.
• Lead first-author papers and write reproducible code.

Skills

Python

MATLAB

Julia

Statistics

Machine learning

Signal processing

Education

PhD in quantitative field

MD with quantitative training

Job description

Mass General Brigham in Boston is seeking a Research Fellow (Postdoctoral) to advance NIH-funded neural dynamics research using large RNS datasets from Brigham and Women’s and Massachusetts General Hospitals. The role centers on turning ECoG data into quantitative brain-state measures and building predictive models of seizure outcomes.

The ideal candidate has a PhD in a quantitative field or an MD with quantitative training, strong coding in Python/MATLAB/Julia, and a track record of