This is an exciting opportunity to join an Innovate UK-funded digital health project. The successful applicant will lead the design of a personalised machine learning platform that leverages the individual rules of thumb that people with diabetes use to manage their own condition in the different situations they face every day: eating, activity, stress, travel, taking a day off, illness, menstruation, etc.
This post is based in the Intelligent Systems Lab (https://intelligentsystems.bristol.ac.uk) and Digital Health Engineering Group (http://www.bristol.ac.uk/engineering/people/group/research_group/5943) at the University of Bristol supervised by Prof. Peter Flach and Dr. Raul Santos Rodriguez. The work will be conducted in collaboration with the diabetes technology start-up Quin Technology (https://quintech.io/). The successful applicant will also work closely with a human computer interaction researcher, based in Bristol's Interaction Group (http://www.biglab.co.uk/) and supervised by Dr Aisling O'Kane and Dr Paul Marshall.
The post will involve engaging users in designing machine learning solutions for the understanding, explaining and interpreting models for the self-management of diabetes. The results of these studies will be written up and submitted to top tier publication venues.
The successful applicant will have experience in implementing state of the art machine learning algorithms and an understanding of interaction...
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The successful applicant will have experience in implementing state of the art machine learning algorithms and an understanding of interaction design with users, and a MSc or PhD in machine learning / data science (or a closely related discipline). They will have experience designing, running, and writing up research activities.
This post is offered full or part time, fixed term contract for up to 17 months starting 1 April 2019.
It is anticipated that interviews will take place in March.
Informal enquiries can be made to: Peter Flach (email@example.com) and Raul Santos Rodriguez (firstname.lastname@example.org)