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Postdoctoral Research Fellow in Computational Neuroscience

Mass General Brigham

Boston, MAFull-time$72–81K/yrPosted 1 day agoStill listed today

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At a glance

Compensation
$72–81K/yr
Location
Boston, MA
Role Type
Fellowship
Schedule
Full-time
Work Authorization
Visa required • Visa sponsorship

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Job overview

This NIH-funded postdoctoral position uses computational methods and a large responsive neurostimulation dataset to investigate why treatment outcomes vary among people with epilepsy. The fellow will analyze chronic ECoG recordings, stimulation histories, brain imaging, and clinical outcomes, and may explore other neurological and psychiatric disorders. The project is based in Boston and offers mentorship, collaboration with clinicians, access to computing resources, and support for fellowship funding applications.

Skills & qualifications

RequiredNice to have

Skills

PythonMATLABJuliaSignal ProcessingStatistical ModelingMachine LearningTime-Series MethodsCausal MethodsNeuroimaging AnalysisNeural Data Analysis

Qualifications

PhD in Quantitative Field or MD With Equivalent Quantitative TrainingFirst-Author Paper or Preprint

Full job description

Site: Mass General Brigham Incorporated

Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.

Job Summary Why does responsive neurostimulation (RNS) leave some people with epilepsy almost seizure-free and others with no benefit? This NIH-funded position (R01NS136297, through November 2029) uses computational methods to find out. You will work with one of the largest RNS datasets: more than 260 patients at Brigham and Women’s and Massachusetts General Hospitals. It includes about 240,000 chronic ECoG recordings, stimulation histories, brain imaging and clinical outcomes. The Mapping & Engineering Neural Dynamics (MEND) Lab is led by neurosurgeon and neuroscientist Dr. John Rolston. We combine electrophysiology, advanced imaging, and electrical stimulation to understand and treat disorders of altered brain activity, including epilepsy, tremors, chronic pain, and psychiatric illness. The R01 project is the priority for this position, but you can also explore other neurological and psychiatric disorders.

Qualifications

To apply Email a CV, a statement of interest, and a link to code that you wrote to [email protected], copying [email protected] and our lab manager ([email protected]). We review applications on a rolling basis.

What you will do

  • 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.

What you need

  • PhD in a quantitative field (computational neuroscience, engineering, computer science, statistics, mathematics or physics), or an MD with equivalent 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. Intracranial experience is valued, but not essential. What we offer Mentorship from Dr. Rolston, with additional day-to-day guidance from Senior Postdoctoral Research Fellow, Dr. Jeremi Chabros. Close work with surgeons and neurologists, hospital CPU and GPU clusters, and support for your own fellowship funding applications. Details Research Fellow (Postdoctoral), full-time. Boston (Longwood), hybrid. Flexible start, early 2027 preferred. J-1 visa sponsorship is available to qualified candidates.

Additional Job Details (if applicable)

The compensation range for this role is between $71,750 - $81,179. Candidate experience is thoughtfully considered throughout the recruitment process, and those with significant experience may be considered for compensation above the starting range listed, as consistent with organizational guidelines and internal equity.

Years of experience 0     $71,750 - $73,544 1     $73,544 - $75,382 2      $75,382 - $77,267 3     $77,267 - $79,199 4+     $79,199 - $81,179

Remote Type

Onsite

Work Location

75 Francis Street

EEO Statement:

0100 Mass General Brigham Incorporated is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law. We will ensure that all individuals with a disability are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. To ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Veteran’s Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact Human Resources at (857)-282-7642.

Mass General Brigham Competency Framework At Mass General Brigham, our competency framework defines what effective leadership “looks like” by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused, half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance, make hiring decisions, identify development needs, mobilize employees across our system, and establish a strong talent pipeline.

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