Real-time spatio-temporal analysis of "big" streaming disease surveillance data for anomaly detection.

We are looking for a motivated graduate to develop statistical models and algorithms to work on real-time big data problems for disease surveillance and outbreak detection. The successful applicant should have a high undergraduate or master’s degree with statistics, data science, or related subjects.

The project will focus on stochastic modelling of the real-time stream of case data from the SAVSNET veterinary disease reporting system, to detect spatial “hotspots” and unusual “spikes” of disease incidence in order to guide clinical practice in terms of diagnosis and treatment. The methodology developed in this project will ultimately become part of the SAVSNET system to provide daily situation reports of the current animal health landscape in England, enabling the risk of zoonotic disease to be quantified.

The successful applicant will undergo training in:
· Spatiotemporal statistical methods, such as Gaussian Processes and infectious disease models;
· Statistical scientific computing in R, Python, and C++;
· Skills in translational science, in particular those of working in a multidisciplinary team.

This project is part of SAVSNET Agile, a wider collaboration with the aim of speeding up the flow of information from disease surveillance measures to clinically relevant decision making for human and animal health. The successful applicant will be encouraged to attend meetings and conferences, and interact with other SAVSNET Agile PhD students at Liverpool and Bristol Universities working in complementary disciplines as well as the rest of the SAVSNET team including software engineers and machine learners.

This project will be based at Lancaster University, working in CHICAS (Centre for Health Informatics, Computing, and Statistics) within Lancaster Medical School: http://chicas.lancaster-university.uk/

A student stipend of £19,037 per annum is available for this project, which will also cover all necessary postgraduate fees.

For more information, contact Chris Jewell or Barry Rowlingson .

Applications: https://www.lancaster.ac.uk/study/postgraduate/postgraduate-courses/statistics-and-epidemiology-phd/

Type
PhD position
Institution
Lancaster University
City
Lancaster
Country
UK
Closing date
September 12th, 2019
Posted on
August 12th, 2019 10:44
Last updated
August 12th, 2019 10:44
Share