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Research Fellow - Artificial Intelligence/Machine Learning

Mass General Brigham

Research Fellow - Artificial Intelligence/Machine Learning

Mass General Brigham

Boston-MA

·

On-site

·

Full-time

·

1w ago

Site: The Brigham and Women's Hospital, Inc.

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:

About Our Lab:

We are an academic research lab operating with a startup mindset, specializing in developing innovative artificial intelligence and machine learning solutions directly integrated into clinical workflows through Epic EHR systems. Our team is dedicated to significantly improving maternal health outcomes through rigorous translational research, emphasizing creativity, rapid professional growth, and measurable real-world impact.

Qualifications:

Role

We are seeking a highly motivated, collaborative individual passionate about developing predictive models that enhance patient safety and prevent adverse pregnancy outcomes. You will utilize multidimensional clinical datasets, including waveform signals (e.g., ECG), genetic data, and imaging, to create predictive algorithms targeting critical maternal outcomes such as hypertensive crises, hemodynamic instability, hemorrhage, and ICU admission. You will also contribute to developing NLP-based and time-series models and integrating these models directly into clinical practice.

Our state-of-the-art data platform provides access to billions of clinical data points from over 300,000 patients, enabling ambitious, publishable work with clear translational pathways.

You will be part of a multidisciplinary team of data scientists, clinicians, and researchers in a stimulating academic environment, with ample opportunities for collaboration across all Mass General Brigham hospitals, Harvard Medical School, the Program in Medical and Population Genetics at the Broad Institute, and industry partners.

Required qualifications

· PhD (completed or near completion) in a quantitative discipline (computer science, biomedical engineering, biostatistics, data science, bioinformatics, or related).

· Strong Python and hands-on deep learning experience (Py Torch or Tensor Flow).

· Demonstrated ability to execute rigorous ML research (clean experimental design, evaluation, reproducibility, clear communication).

· Depth in at least one of the following, with readiness to extend methods into adjacent areas as needed:

o time-series / waveform ML

o medical imaging AI (ultrasound experience is a plus)

o interpretability / error analysis for clinical ML

o multimodal fusion / clinical deployment-oriented ML

How to apply

Email vkovacheva@bwh.harvard.edu with subject “Application for AI/ML postdoc position” and include: CV, cover letter (research background + interests), and 3 references.

Additional Job Details (if applicable)

Remote Type

Onsite

Work Location

45 Francis Street

EEO Statement:

2200 The Brigham and Women's Hospital, Inc. 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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About Mass General Brigham

Mass General Brigham

Mass General Brigham Inc. is a not-for-profit, integrated health system based in Greater Boston. It operates two academic medical centers—Massachusetts General Hospital and Brigham and Women's Hospital—along with specialty and community hospitals, home care, urgent care, and a licensed health plan...

10,001+

Employees

Boston

Headquarters

Reviews

3.8

36 reviews

Work Life Balance

3.9

Compensation

3.8

Culture

3.8

Career

4.0

Management

3.7

74%

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Pros

Good work-life balance and flexible environment

Competitive compensation and benefits

Opportunity for career growth

Cons

Some organizational bureaucracy

Room for improvement in processes

Internal communication could improve

Salary Ranges

56 data points

Junior/L3

Mid/L4

Junior/L3 · Licensing Manager I

1 reports

$140,300

total / year

Base

$122,000

Stock

-

Bonus

-

$140,300

$140,300

Interview Experience

41 interviews

Difficulty

3.2

/ 5

Duration

14-28 weeks

Offer Rate

40%

Experience

Positive 69%

Neutral 12%

Negative 19%

Interview Process

1

Phone Screen

2

Technical Interview

3

Hiring Manager

4

Team Fit

Common Questions

Technical skills

Past experience

Team collaboration

Problem solving