Master / PhD Scholarship in Machine Learning for Embedded IoT Devices

Applications are invited for a fully funded 4-year PhD/ 18- month M.Eng position at the Internet of Things lab at University College Dublin, Ireland. Scholarship cover tuition fees and a tax free stipend of €18,000 per year.

Background

Health care expenditure has been drastically increasing worldwide over the past several years, due to an aging population and chronic conditions. Continuous and pro-active monitoring of vital health signals using wearable sensors are widely seen as a solution. However, there are several challenges involved in making wearable sensors a ubiquitous reality. These include the large power consumption of the sensors due to continuous monitoring, low data acquisition quality due to motion artefacts etc.
This project aims at developing embedded machine learning and signal processing techniques for power reduction in wearable devices. The project will investigate syntactic / machine learning based methods for anomaly detection from real time streaming biomedical data. The techniques developed will be deployed and tested in an embedded wearable sensor to experimentally measure the improvements.
The project will involve collaboration with multi-disciplinary researchers who are working on wireless sensor IoT system design, low power circuit design, machine learning and data analytics, clinicians etc. The position also provides the opportunity to gain valuable experience in design, fabrication and testing of embedded wearable devices. The successful candidate will get opportunities for presenting their work in international conferences and workshops, and publication of the research in high impact journals.

Applicants for this position should ideally have:

• A first / upper 2nd class honours BE degree in: Electrical /Computer Engineering or equivalent.
• Strong analytical skills and good knowledge in Matlab and C programming.
• Knowledge / research background in signal processing, machine learning, Embedded software/system development. Industrial experience will be an advantage.
• Good interpersonal, communication and English language skills.
• Be enthusiastic and willing to learn new concepts and ideas.

How to Apply
The project will be supervised by Dr. John, Dr. Barry. Applications consisting of a cover letter, Transcripts, contact details of 3 referees, and curriculum vitae should be sent to [Email Address Removed]