PhD studentship in Neonatal Monitoring and Data Analytics

Cambridge; Cambridge; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading educational institution in the UK is offering a PhD studentship focused on Neonatal Monitoring and Data Analytics. The role involves developing algorithms for real-time processing, applying big data analytics to clinical datasets, and integrating data streams to enhance patient care. Candidates should hold a first or upper second-class degree in engineering or computer science, and possess a keen interest in medical technology. This opportunity provides funding for a three-year period and aims to advance neonatal care through innovative solutions.

Qualifications

• A demonstrable interest in medical technology and healthcare innovation is essential.
• Applicants with relevant research experience are strongly encouraged to apply.
• Good communication skills and ability to work collaboratively are desirable.

Responsibilities

• Develop algorithms for real‑time signal processing and anomaly detection.
• Apply big data analytics and deep learning to NICU datasets for predictive modelling.
• Investigate integration of multimodal data streams to support decision-making.

Skills

Real-time signal processing

Anomaly detection

Big data analytics

Machine learning

Embedded electronics

Signal processing

Wireless systems

Education

First or upper second-class degree in engineering, computer science or related discipline

Job description

PhD studentship in Neonatal Monitoring and Data Analytics

The post is joint appointment between the University of Cambridge Departments of Engineering and Paediatrics.

Start Date: 17 April 2026

Application Deadline: 14 January 2026

Funding Duration: 3 years (Home fee rate only)

Project Overview

Neonatal intensive care (NICU) presents unique challenges in monitoring vital signs while supporting developmental and psychological needs of preterm infants and their families. Current wired monitoring systems create physical and emotional barriers, limiting parental contact and increasing stress. Evidence shows that improving physical contact through wireless monitoring can enhance breastfeeding rates, reduce hospital stay, and improve neurodevelopmental outcomes. The collaboration between the Department of Paediatrics and Engineering has been exploring novel continuous monitoring systems to support a more holistic approach to care. This has included non‑contact monitoring specifically designed for use in the unique setting of NICU and uses an RGB‑D (red‑green‑blue‑depth) camera to monitor the infant. The cameras contain a visible light sensor (RGB), and a depth sensor (D). The successful applicant will join the team exploring data science and AI for neonatal care. Areas of work will include:

Responsibilities

• Development of algorithms for real‑time signal processing and anomaly detection,
• Applying big data analytics and deep learning to NICU datasets for predictive modelling of clinical outcomes,
• Investigating integration of multimodal data streams to support decision‑making and improve patient care.

Qualifications

Candidates should have a first or upper second‑class degree in engineering, computer science, or a related discipline. A demonstrable interest in medical technology and healthcare innovation or one of the following: wireless systems, embedded electronics, signal processing, machine learning, or big data analytics is essential, as is an interest in working with health‑care related data. Applicants with relevant research experience, gained through Master’s study or laboratory work, are strongly encouraged to apply. Motivation, creativity and intellectual independence are desirable, as are good communication skills and the ability to work collaboratively.

Application Instructions

• Apply for the PhD in Paediatrics and specify the project title: "Continuous Monitoring and Data Analytics in Neonatal Care".
• It is not necessary to contact potential supervisors before applying.
• You also do not need to upload a research proposal as the project is already set - this section can be used to give additional supporting information for your application, or a blank proposal can be uploaded.

The funding for this post is available for 3 years. Funding covers the student’s stipend and tuition fees at the Home rate. Due to the amount of funding available, we can only offer this studentship to students who are eligible for the Home fee rate.

Applications must be submitted via the University Applicant Portal.

Please quote reference RP48204 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.