Research Fellow - Artificial Intelligence/Machine Learning

Mass General Brigham • Boston, MA

1d • Onsite

About The Position

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.

Requirements

• 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 (PyTorch or TensorFlow).
• 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

Nice To Haves

• ultrasound experience

Responsibilities

• 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.
• Contribute to developing NLP-based and time-series models and integrating these models directly into clinical practice.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree