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 Digital Acoustic Analysis, Music Technology, Health Surveillance, Wearable Sensors, Machine Learning, Artificial Intelligence (AI) and related basic science.
Audio recorded by smartphones can be used to detect various respiratory illnesses. For example, changes in the fundamental frequency and excitation cycle of the speech signal and changes in vocal tract airflow can be detected by analysing audio recordings, and these changes can be linked with respiratory diseases. Additionally, certain patterns in pitch, formant frequencies, and loudness have been connected with COPD and asthma. The short-term power spectrum of the speech signal has also been analysed to obtain spectral information corresponding with respiratory diseases. Moreover, some machine learning techniques have been developed to automate disease detection from audio recordings. This project will aim to translate Digital Acoustic Analysis to Covid and Health Surveillance, and it will foster a deeper understanding of related fundamental topics including Digital Health, Respiratory and Cardiac Sound Analysis, Wearable Sensors, Machine Learning, and Artificial Intelligence (AI).
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 physiological 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.
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