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PhD Studentship - Characterising Behaviour from Sensor Data

University of Bristol

Qualification Type: PhD
Location: Bristol
Funding for: UK Students, EU Students
Funding amount: see advert
Hours: Full Time
Placed On: 11th January 2019
Closes: 1st October 2019
 

Location: Computer Science, Bristol

Funding amount

Minimum £14,777 p.a. for 3 years subject to confirmation and eligibility status

The project:

This fully-funded post is part of the MRC-funded CUBOID project that is developing novel behavioural models to passively detect signatures of dementia from unobtrusive in-home sensor networks. CUBOID's aims are to demonstrate that passive monitoring will reveal previously unseen behavioural biomarkers of early Alzheimer’s disease. CUBOID will leverage the state-of-the-art SPHERE in-home sensing platform in a longitudinal data capture campaign to acquire data from several sensing modalities (including, but not limited to): environmental (e.g. PIR, temperature, humidity), RGB-D (e.g. silhouette, bounding box), on-body (e.g. accelerometer), voice and text. As well as sensor data, clinical evaluations will also be performed (including neurophysiological tests, brain imaging) over a 12-month period starting in mid-2018.

We are seeking an exceptional candidate to take up a PhD studentship focusing on machine learning and healthcare analysis for early diagnosis/tracking of Alzheimer's disease. The successful applicant will benefit from close interaction with the growing digital health groupintelligent systems lab and the wider interdisciplinary digital health team at the University of Bristol.

How to apply:

Please make an online application for this project at www.bris.ac.uk/pg-howtoapply. Please select < Computer Science> on the Programme Choice page and enter details of the studentship when prompted in the Funding and Research Details sections of the form with the name of the supervisor

Candidate requirements: 

A minimum 2.1 or first-class degree in Mathematics, Computer Science Engineering or a related discipline.

The ideal candidate will have basic skills and knowledge in machine learning; signal processing, data processing/visualisation.

Funding:

Scholarship covers full UK/EU (EU applicants who have been resident in the UK for 3 years prior to 1st September 2018) PhD tuition fees and a tax-free stipend at the current RCUK rate (£14,777 in 2018/19). EU nationals resident in the EU may also apply but will only qualify for PhD tuition fees.

Contacts:  

For informal enquiries, please contact Dr Niall Twomey (niall.twomey@bristol.ac.uk) or Dr Raul Santos-Rodriguez (enrsr@bristol.ac.uk)

For general enquiries, please email sceem-pgr@bristol.ac.uk

   
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