Machine Learning Scientist - Human Physiology & Biomarkers

Pioneering Medicines; Cambridge (MA); On-site; USD 136,000 - 212,000; Full time

Benefits offered by this job

Healthcare coverage

Retirement benefits

Annual incentive program

Comprehensive benefits

Job summary

FL127, part of the Flagship Pioneering ecosystem, seeks a Scientist, Machine Learning (Human Physiology) in Cambridge, MA to connect physiological signals our platform measures with outcomes in small human cohorts. You will co-design studies with the imaging team and build models linking measurements to reference measures.

We seek a PhD with deep physiology knowledge and strong Python/ML skills to work with AI agents in literature synthesis, study design, data analysis, and coding within an

Qualifications

• PhD in biomedical engineering, physiology, bioengineering, biophotonics, or a related field, or an MD/PhD, with substantial applied machine learning experience.
• Deep knowledge of human physiology in areas such as microcirculation, hemodynamics, tissue optics, skin biology, or cardiorespiratory physiology.
• Experience taking a measurement or digital biomarker through human studies, including endpoint selection, reference measurements, IRB-governed protocols, and agreement analysis.
• Statistical modeling on small human datasets, including within-subject and longitudinal designs.
• Proficiency in Python and the modern ML stack, and comfort working inside an existing research codebase.
• Imaging and signal-processing background to reason about calibration, registration, and sampling effects on derived measurements.
• Ability to work independently in an early-stage, ambiguous environment and make decisions with incomplete data.

Responsibilities

• Ground each measured signal in physiology and identify what it reflects and confounds.
• Collaborate with product/market teams to select applications to study first based on plausibility, cost, and value.
• Co-design human studies with imaging team, defining endpoints, reference measurements, and protocols.
• Build and evaluate models relating measurements to reference measures and outcomes in small cohorts, addressing confounders and demographic factors.
• Set the evidence bar for findings to influence products and report strengths/limitations of data.
• Review extracted signals for physiological plausibility and suggest improvements to the measurement pipeline.

Skills

Python

Machine learning

Statistics

Signal processing

Education

PhD in biomedical engineering or related field

Job description

FL127, part of the Flagship Pioneering ecosystem, seeks a Scientist, Machine Learning (Human Physiology) in Cambridge, MA to connect physiological signals our platform measures with outcomes in small human cohorts. You will co-design studies with the imaging team and build models linking measurements to reference measures.

We seek a PhD with deep physiology knowledge and strong Python/ML skills to work with AI agents in literature synthesis, study design, data analysis, and coding within an