Photoplethysmography (PPG) AI Data Scientist in Health (KTP Associate)

City, University of London

London

2 months ago

Applications closed

Background

CSGUoL and InfoHealth Ltd are recruiting for a candidate to transform non-invasive continuous blood pressure monitoring by developing personalised AI models and algorithms incorporating Photoplethysmography (PPG) measurements

Working at InfoHealth’s offices in Coulsdon, Surrey, with visits to CSGUoL, the candidate will apply their academic and commercial knowledge to this critical project.

InfoHealth has developed a digital product called NowPatient within which patients can book GP appointments, view medical records, and access NHS services conducted via virtual video consultations. The KTP will support InfoHealth to add to the capabilities within NowPatient, enabling InfoHealth to embed AI and Machine Learning methodologies, optimising current and new products/services.

Responsibilities

The candidate will work with advanced PPG signal processing and PPG Pulse wave Analysis (PWA) and modelling frameworks using ML/AI and develop clinical standards and ethics procedures for validation criteria.

Specifically, the candidate will investigate current development platforms for wearables using optical sensing, collect and curate data, incorporate adaptive AI models, and develop a deep learning architecture.

Person Specification

We are looking for a candidate with an MSc or other Higher Degree in Electrical/Biomedical Engineering, Computer Science or relevant field, with a focus on time series data analysis, algorithm design and implementation. Knowledge of programming (Python) and AI platforms is essential, as is experience of planning and conducting complex experimental research projects.

The ideal candidate will have knowledge of PPG, real-time processing of PPG data, and medical validation standards, as well as experience of developing predictive algorithms for wearables and experience with publicly available databases or medical datasets to validate and compare models.

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