| The Oxford University Big Data Institute (BDI) is a new interdisciplinary research centre aiming to develop, evaluate and deploy efficient methods for acquiring and analysing biomedical data at scale and for exploiting the opportunities arising from such studies. The Nuffield Department of Population Health (NDPH), a key partner in the BDI, contains world-renowned population health research groups and is an excellent environment for multi-disciplinary teaching and research.
Based within the BDI building, you will be part of initiative to create new open source digital phenotyping methods for brain health. This will entail: creating probabilistic models to analyse responses from tasks, apps and games; producing statistical analyses across large populations of users; working with a variety of data streams including, motion, voice, text, location and touch; building visualisations and analytic tools for other analysts to use; collaborating with other data scientist around the world on analyses of open datasets; working with brain imaging experts on combined analyses; and, collaborating with software engineers to both scale up analyses so they can be applied across millions of participants, and build analytic algorithms directly into apps.
To be considered you will have a PhD involving a substantial data science component and a BSc or MSc in science, maths, engineering or computing. You will require a strong understanding of statistical methods for analysing longitudinal data, and must be able to demonstrate instances of solving significant scientific problems using data science techniques.
Informal enquiries should be addressed to Dr Chris Hinds (chris.hinds@bdi.ox.ac.uk).
The position is full-time (part-time considered) and fixed-term for 2 years.
The closing date for applications is 12.00 noon on 19 February 2018. |