Job Description

GENERAL SUMMARY/ OVERVIEW STATEMENT: Summarize the nature and level of work performed.

Our laboratory applies computational, and machine learning methods to understand the impact of seizures and abnormal brain activity on outcomes in critically ill patients with brain injury. Our goal is to improve treatment strategies and the clinical care of these patients. Analysis of large datasets (including EHR datasets, hospital and claims based databases) and neurophysiology data (including electroencephalopgraphy-EEG) is central to these efforts.

Specific efforts focus on developing methods for automatically abstracting data including clinical variables (eg medication doses, radiology, laboratory data) and clinical outcomes (eg medication adverse effects) on a large scale; creating tools to predict clinical outcomes in patients with seizures and abnormal EEG patterns treated with anti-seizure medications; and understanding the relationships between abnormal patterns of brain activity (EEG patterns) and neurological deterioration. Efforts will also focus on creating tools for data mining of structured and unstructured clinical data, including free text reports and clinical notes. Efforts will include signal processing, including EEG data processing and annotation.

The ideal candidate will have excellent analytical and troubleshooting skills, knowledge of software development methodologies and systems design, and a desire to solve complex and large-scale problems to make important scientific and technical contributions to medicine.

PRINCIPAL DUTIES AND RESPONSIBILITIES: Indicate key areas of responsibility, major job duties, special projects and key objectives for this position. These items should be evaluated throughout the year and included in the written annual evaluation.

This position involves a range of opportunities, including:

- Analysis of EEG and other physiological time series data

- Statistical modeling and analysis of diverse medical data

- Software development and code management

- Management of a large physiological database

- Management of a multi-center electronic health record database

Qualifications

SKILLS/ABILITIES/COMPETENCIES REQUIRED: Must be realistic, objective, measurable and related to essential functions of this job.

We are seeking a full-time postdoctoral fellow with a strong interest in applying clinical research and medical informatics. Applicants should possess a PhD in a relevant discipline (computer science, machine learning, epidemiology, electrical engineering, or applied mathematics) and have established an excellent research profile in signal processing or machine learning. This position is initially available for a period of two years.

In addition, the ideal applicant should have a strong programming background (e.g. Python, R, SQL, MATLAB) and the drive and enthusiasm to learn about clinical neuroscience by assisting in state-of-the art patient-centered research.

LICENSES, CERTIFICATIONS, and/or REGISTRATIONS (if applicable): Specify minimum credentials and clearly indicate if preferred or required

None.

EDUCATION: Specify minimum education and clearly indicate if preferred or required

PhD in a relevant discipline such as statistics, machine learning, electronic engineering, computer science, or applied mathematics.

EXPERIENCE: Specify minimum creditable years of experience and clearly indicate if preferred or required

A PhD or equivalent degree is required.

SUPERVISORY RESPONSIBILITY (if applicable): List the number of FTEs supervised.

The candidate will work within a team of physicians, clinical research coordinators, and biomedical and electrical engineers, and computer scientists. May share responsibility for mentoring more junior lab members.

FISCAL RESPONSIBILITY (if applicable): Indicate financial \xe2\x80\x9cscope\xe2\x80\x9d information, i.e.: size of budget, volume, revenue, etc.; Indicate total physician/non-physician FTE scope

The candidate will not have budgetary responsibility but will need to design projects and identify equipment for projects within a budgetary scope and in liaison with a staff assistant performing purchase orders.

WORKING CONDITIONS: Describe the conditions in which the work is performed.

Work will be performed in several of the MGH Intensive Care Units and in laboratory space on the MGH campus.

Mass General Brigham