Department of Computer Science and Technology, West Cambridge

Probabilistic Machine Learning for Mobile and Wearable Health Data and Systems

The EPSRC Centre for Doctoral Training in Sensor Technologies for a Healthy and Sustainable Future, in collaboration with Arm, is inviting applications for a fully funded 1+3 years MRes + PhD studentship, commencing in October 2021. The studentship will be hosted by Professor Cecilia Mascolo's group (https://mobile-systems.cl.cam.ac.uk) in the Department of Computer Science and Technology.

This project will investigate the general area of probabilistic machine learning in the context of wearable data and systems. The area offers unique challenges related to estimation of uncertainty in the context of wellbeing and clinical applications as well as with devices which generally offer considerably constrained resources. During the first year of the programme, the student will identify specific objectives and write a project proposal under the guidance of Prof. Mascolo.

Mobile and wearable devices use is soaring, and their sensing capabilities are expanding. The data they produce can be very valuable in the investigation of user's wellbeing in general and more precisely of their health. Mascolo's team has investigated various aspects of this research area ranging from data specific challenges to the machine learning (automatic model adaptation, automatic labelling, missing data resilient approaches) or to the systems aspects of on device model computation. The group also researches at the level of innovative sensing modalities for specific applications.

The studentship is fully-funded for 4-years and will be hosted at the University of Cambridge in the Department of Computer Science and Technology. The student will be enrolled in the Centre for Doctoral Training in Sensor Technologies for a Healthy and Sustainable Future (http://cdt.sensors.cam.ac.uk). The first year involves a highly interdisciplinary programme consisting of lectures, research and team projects covering a wide range of technologies sensing and imaging. Successful completion of the first year will lead to a Master of Research qualification (MRes) and optimal preparation for the PhD project in years 2-4. We are seeking a highly motivated individual with a strong academic background, as demonstrated with a 1st class degree, or equivalent, in a Computer Science or Computer Engineering. The candidate will have demonstrable knowledge in machine learning and possibly experience with mobile and wearable or sensing data.

https://www.jobs.cam.ac.uk/job/29388/