Research Fellow (81456-018)

University of Warwick - Department of Mathematics

Fixed term contract for 13 months.

Applications are invited for a postdoctoral research fellow to work with Dr Sebastian Vollmer and his group within the framework of the Alan Turing Institute’s project on using data science for emergency departments. This includes preventing admissions to A&E by better risk scoring and better use of resources within A&E process. This collaborative effort includes Louis Aslett, Franz Kiraly, Ioanna Manolopoulou and Bilal Mateen.

The SPARRA (Scottish Patients at Risk of Readmission and Admission) model, which is used by NHS Scotland as a decision support tool to identify patients at risk of hospital admission, was the subject of a week-long data study group (DSG) hosted at The Alan Turing Institute in September 2017.

During the DSG, modern statistical machine learning methods were applied to monthly aggregated panel data subsampled from among 1.8 million patients over a 5 year period. The results of this week-long DSG exercise demonstrated substantial improvements in both sensitivity and specificity of emergency hospital admission predictions compared to SPARRA scores, which are currently utilised on a nationwide basis by general practitioners.

This project flows from the findings of the DSG. In particular, one primary objective is to fully develop a deployment ready state-of-the-art machine learning tool for emergency admission risk and ranking. This will involve modelling the full population dataset, with extensive feature selection, as well as feature engineering in conjunction with expert medical input.

The ideal candidate will have a strong background in data science and/or related fields

During the DSG, modern statistical machine learning methods were applied to monthly aggregated panel data subsampled from among 1.8 million patients over a 5 year period. The results of this week-long DSG exercise demonstrated substantial improvements in both sensitivity and specificity of emergency hospital admission predictions compared to SPARRA scores, which are currently utilised on a nationwide basis by general practitioners.

This project flows from the findings of the DSG. In particular, the primary objective is to fully develop a deployment ready state-of-the-art machine learning tool for emergency admission risk and ranking. This will involve modelling the full population dataset, with extensive feature selection, as well as feature engineering in conjunction with expert medical input.

The ideal candidate will have a strong background in data science and/or related fields.

Closing date: 28 February 2018

Full details of the duties and selection criteria for this role are found in the vacancy advert on the University of Warwick jobs page. You will be routed to this when you click on the Apply button below.

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Midlands of England