Research Scientist – Maternal Sleep

Overview

In this role you will lead EMBRACE’s maternal sleep programme, focusing on obstructive sleep apnoea and nocturnal hypoxaemia in pregnancy and their impact on maternal and perinatal outcomes. You will design and deliver observational and interventional studies, secure external funding, and translate findings into antenatal screening and treatment pathways. You will collaborate across disciplines and partners to develop AI-enabled, scalable research. This is a non-clinical, fixed-term post with a focus on meaningful impact.

Pay / Benefits

• professional development days (pro-rata)
• London Weighting
• salary £53,947 – £63,350
• non-clinical/basic science post
• opportunity to impact maternal health

Responsibilities

• Design and deliver observational cohort studies and interventional trials of sleep-disordered breathing in pregnancy
• Secure external research funding and translate findings into antenatal screening and treatment pathways
• Collaborate with clinicians, data scientists, behavioural scientists and international partners to run AI-enabled research studies
• Develop scalable study designs and protocols across EMBRACE partner sites
• Manage projects across multidisciplinary teams to meet tight deadlines
• Present findings at conferences and contribute to publications and grant applications

Key requirements

• PhD in relevant field with postdoctoral experience
• Knowledge of maternal and perinatal outcomes and objective sleep measurement (PSG and/or home sleep apnea testing)
• Experience designing and delivering clinical, behavioural, population health, or digital health studies with ethics approvals
• Track record of peer-reviewed publications and grant applications
• Project management skills and ability to lead multi-disciplinary teams

• cross-disciplinary collaboration
• communication and stakeholder engagement
• ability to work under tight deadlines
• polysomnography (PSG) and home sleep apnea testing
• longitudinal analysis with R or Python
• handling large maternity datasets and data linkage

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