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Research Assistant / Associate at Imperial College London

A new openingpostdoctoral researcher position in computer science is available at Imperial College London, UK. Applications are welcome before October 25, 2018.

We are seeking outstanding candidates to work on a two-year project to develop statistical tools to predict and understand the dynamics of NHS hospital attendance at St Mary's Hospital in Paddington, London.

Managing and predicting the rates of admission along with the duration of stay at emergency departments (collectively referred to as demand), is essential for preventing infection, planning rosters for staff and in the financial and strategic planning. A failure to make provision for surges in demand leads to overcrowding, which has been linked to adverse patient outcomes, poor access to care and diseconomies of scale. Despite its importance, methods for predicting demand and understanding the underlying dynamics have not been well studied.

We seek an exceptional and technically proficient Research Assistant or Associate to utilise the current state-of-the-art techniques from machine learning and statistics to investigate:
- To what degree is demand fundamentally predictable from an information theoretic and entropy view.
- What statistical architecture best captures the underlying temporal process (e.g ARIMAs, Smoothing, Long short term memory/GRU recurrent nets, seq2seq architechtures etc.)
- What quantitative accuracy can be expected from forecasts and how this degrades with the level of aggregation and time horizon of the forecast,
- By collecting accessory data, and including random effects, what are the underlying factors contributing to changes in demand,
- Can detailed calendar information such as school holidays, weather, and public events be used to leverage predictive accuracy
- Is it possible to characterise the frequency and occurrence of anomalous surges of excessive demand
- Can our framework be applied efficiently in near-real time settings.

New methods and models will be expected to directly inform practitioners within St Mary's hospital.

Applicants should have an MSc (for appointment to Research Assistant) or PhD (for appointment to Research Associate) or equivalent in one of the following areas: statistics, mathematics, machine learning, economics, computer science or a similarly quantitative discipline. You will have research experience in time series analysis / methods and in machine learning. You should also have experience with modern statistical inference tools such as Stan, TensorFlow, etc.

The post will be based within the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis and affiliated with the Imperial College Data Science Institute.

This post is full time and fixed term until 31 October 2020 and will be based at the St Mary's Campus, Paddington. Imperial College is supportive of flexible working. The College is happy to discuss the possibility of implementing such arrangements for this post, with suitably qualified people, subject to operational requirements.

Should you have any queries please contact: Dr Sam Bhatt (s.bhatt@imperial.ac.uk) or Dr Seth Flaxman (s.flaxman@imperial.ac.uk).


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