Postdoctoral Fellow
Postdoctoral Fellow
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Job Description
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.
(Artificial Intelligence/Machine Learning)
Job Summary
Application and inquiries should be submitted by e-mail to Dr. Kovacheva with Application for AI/ML postdoc position in the subject line. Along with your CV please include a cover letter describing previous research research interests and future goals. Please provide contact details for 3 references.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
Application and inquiries should be submitted by e-mail to Dr. Kovacheva with Application for AI/ML postdoc position in the subject line. Along with your CV please include a cover letter describing previous research research interests and future goals. Please provide contact details for 3 references.
Position Description
A postdoctoral fellowship is immediately available in the research group led by Dr. Vesela Kovacheva in the Department of Anesthesiology at Harvard Medical School / Brigham and Womens Hospital.
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 datasetsincluding waveform signals (e.g. ECG EEG) genetic data and imagingto 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 300000 patients enabling groundbreaking research with immediate translational potential.
You will be part of a diverse 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.
Qualifications
Qualified candidates should have:
- Ph.D. in a quantitative discipline such as data science bioinformatics computer science biomedical engineering or a related field (preferably completed within the last 3 years).
- Strong programming skills in Python with proficiency in deep learning frameworks (PyTorch or TensorFlow) and other data-processing libraries (Polars)
- Demonstrated expertise in machine learning deep learning explainable AI (XAI) and analysis of time-series data.
- Experience in medical imaging analysis with AI
- Familiarity with ultrasound image preprocessing feature extraction and multimodal data fusion using relevant libraries (MONAI ITK OpenCV scikit-image).
- Experience implementing AI interpretability methods (SHAP attention visualization etc).
- Excellent oral and written communication skills meticulous attention to detail and strong professional integrity.
Additional Job Details (if applicable)
Remote Type
Work Location
EEO Statement:
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.
Employment Type
Full-Time
