Biomedical ML Intern — Hybrid, Paid, FT Path

CranioSense, LLC; Boston (MA); Hybrid; USD 62,000 - 83,000; Part time

Benefits offered by this job

Paid internship

Potential for full-time employment

Job summary

CranioSense, LLC is seeking a PhD-level Data Science & Machine Learning Engineer intern to develop advanced algorithms from optical waveform and sensor data. You will estimate intracranial pressure from PPG, build preprocessing pipelines, and extract robust features for predictive modeling.

The role offers independence, mentorship, and potential conversion to full-time. The internship is 4–6 months, hybrid in the Greater Boston Area, with compensation of $45–$60/hour and a path to full-time

Qualifications

• PhD candidate nearing completion (≤24 months) in a quantitative field.
• Experience developing ML/analytical algorithms from physiological or time-series data.
• Background in biomedical signal processing and feature extraction.
• Preference for biophotonics datasets or optical sensing data.

Responsibilities

• Develop and optimize ML and advanced signal-processing algorithms using physiological datasets.
• Estimate intracranial pressure from PPG waveforms and related signals.
• Design preprocessing pipelines to filter, normalize, and analyze raw data streams.
• Extract robust features and guide model development with biophysical reasoning.
• Build and evaluate ML, deep learning models for physiological data interpretation.

Skills

Machine Learning

Python

MATLAB

Signal processing

Time-series analysis

Education

PhD (nearing completion)

Tools

Python environments (AWS/Azure/GCP)

MATLAB

Job description

CranioSense, LLC is seeking a PhD-level Data Science & Machine Learning Engineer intern to develop advanced algorithms from optical waveform and sensor data. You will estimate intracranial pressure from PPG, build preprocessing pipelines, and extract robust features for predictive modeling.

The role offers independence, mentorship, and potential conversion to full-time. The internship is 4–6 months, hybrid in the Greater Boston Area, with compensation of $45–$60/hour and a path to full-time