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Wearable Sensors, Machine Learning and Artificial Intelligence for Healthcare Internet of Things applications

   Department of Electronic Engineering

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  Prof Z Tse  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

The Medical Robotics Lab at the University of York has career opportunities in the area of Medical Robotics and Medical Mechatronics. Applications are invited for a PhD student in Wearable Sensors, Machine Learning, artificial intelligence (AI) and related basic science.

The project is part of an ambitious world-wide research programme supported by Wellcome Leap, which researches the development of executive function and the underlying neural networks in the first 1000 days of life. The successful applicant will work closely with a team of interdisciplinary researchers including developmental neuroscientists, computer scientists, biomedical engineers and statisticians. The overarching goal would be to develop wearable sensors and related artificial intelligence for monitoring infants’ and toddlers’ real world natural statistics relevant for developing healthy executive functions.

We would particularly welcome applications from candidates with background and interest in wearable sensors, artificial intelligence, machine learning, data analytics and modeling, body sensing network, medical IoT, healthcare smartphone applications, medical mechatronics and instrumentation. Other areas of interest include but are not limited to real-time and remote monitoring of heart rate, ECG, respiration rate, sleep pattern, body motion and other health data, fabrication of wearable electronics and flexible sensors, medical signal processing, mobile health and wireless sensor designs. Publication of results is also an integral part of the positions.

Key areas of research include:

  • Design, development and experimental validation of wearable sensors and algorithms for human daily activities and cognitive behaviours
  • Integration of novel and established machine learning and artifact intelligence tools for understanding human physiology
  • Validation of developed wearable sensor and algorithms in collaboration with clinical partners

We are interested in candidates with a strong background in one or more of the following areas:

  • Degree in Mechanical, Electronic, Electrical, Biomedical Engineering, Physics, Computer Science or related fields
  • Hands-on experience in Wearable Sensors, IoT Healthcare Devices, Medical Instrumentation, Medical Mechatronics or working towards or substantial equivalent experience.
  • Demonstrated capability in designs, fabrications, and testing of novel sensors
  • Hands-on experience of 3D printing, laser cutting, 3D scanning and rapidprototping
  • Demonstrated capability in smartphone programming and internet of things (IoT) applications

In addition, the following skills and experience would be a plus:

  • Knowledge in biomedical signal processing (ECG, EMG, EEG, Heart Rate, Respiration Rate, etc.)
  • Programming experience in Python, Android Studio, Xcode, App Inventor, C#
  • Previous experience in medical device prototyping

Candidates will conduct research in the area of minimally invasive interventions in close collaboration with clinical partners.

Entry requirements:

Candidates must have (or expect to obtain) a minimum of a UK upper second class honours degree (2.1) or equivalent in Mechanical, Electronic, Electrical, Biomedical Engineering, Physics, Computer Science or related fields.

How to apply:

Applicants should apply via the University’s online application system at https://www.york.ac.uk/study/postgraduate-research/apply/. Please read the application guidance first so that you understand the various steps in the application process.

Funding Notes

This is a self-funded project and you will need to have sufficient funds in place (eg from scholarships, personal funds and/or other sources) to cover the tuition fees and living expenses for the duration of the research degree programme. Please check the Electronic Engineering website View Website for details about funding opportunities at York.
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