Research Associate AI physical modeling Medical

1 week ago


McLean, Virginia, United States MSAI LABS Full time

This is a full-time remote role for a
Research Associate in Signal Processing and Physiological Modeling
, specializing in HD5y files extracted from hospital ICU machines. The incumbent will lead advanced research in signal processing and physical body flow modeling, with a focus on trauma patient data. Responsibilities include developing and implementing algorithms that link ECG and PPG signals to circulatory and systemic flow dynamics, particularly under acute stress conditions.

This is a
government-sponsored Research Associate role
, offering the unique opportunity to contribute to federally backed trauma research. Unlike equivalent university posts, this position can also provide
stock options as an incentive
, aligning long-term rewards with the growth of MSAI LABS.

Day-to-day tasks involve:

  • Programming and algorithm development for physiological signal interpretation
  • Applying pattern recognition and denoising techniques to trauma-linked biosignals
  • Modeling circulatory flow and systemic responses using multi-modal data
  • Collaborating with cross-functional teams to advance the lab's trauma-focused AI research objectives

Qualifications

  • Strong foundation in Python and/or R
  • Experience modeling physical body flow dynamics using biosignals (ECG, PPG, BP, etc.)
  • Familiarity with trauma physiology and acute care signal patterns
  • Optimization skills for running models on cloud GPU/CPU instances
  • Knowledge of autoencoders, SFFT, or other denoising methods
  • Expertise in pattern recognition and physiological signal interpretation
  • Proficient in programming languages relevant to signal processing and modeling
  • Solid understanding of mathematics, especially as applied to dynamic systems and signal flow
  • Strong analytical and problem-solving skills
  • Ability to work independently and remotely
  • Excellent written and verbal communication skills
  • Experience in a research environment is a plus
  • Master's or Ph.D. in a related field such as Biomedical Engineering, Computer Science, Electrical Engineering, or Applied Mathematics


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