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Postdoctoral Fellow at Brigham and Women’s Hospital  

Harvard Medical School 

(Signal Processing/Machine Learning)

 

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.

 

Role

We are seeking a Postdoctoral Fellow with a PhD degree who has strong hands-on experience in signal processing, waveform analysis, time-series modeling, and Python-based machine learning. This role is ideal for someone who has worked with physiological or biomedical signals such as ECG/EKG, pulse oximetry, plethysmography, fetal heart rate or cardiotocography tracings, arterial line waveforms, and more.

 

The strongest candidate will be comfortable taking messy real-world waveform data and turning it into reliable features, models, visualizations, and reproducible analyses. Prior experience with clinical data is a major plus, but we are also interested in candidates from biomedical engineering, electrical engineering, computer science, statistics, applied math, physics, or data science who have strong signal-processing foundations and are motivated to work in healthcare.

 

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 degree (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). 
  • Hands-on experience with signal processing or time-series analysis.
  • Expertise using SciPy, NumPy, wfdb, NeuroKit2, pyHRV, tsfresh, PyWavelets, or similar tools.
  • Experience working with noisy real-world data, including missingness, artifacts, irregular sampling, or sensor-quality issues. 
  • Familiarity with machine learning model development, evaluation, and reproducible analysis. 
  • Ability to communicate clearly with both technical and clinical collaborators. 
  • Strong ownership, curiosity, and willingness to learn quickly in a fast-moving research environment.

 

Salary range $60,000-$70,000 depending on expertise and experience.

 

How to apply

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