Research Fellow

We are seeking a full-time Research Fellow to support the NIHR ARC Wessex project FORTH – FORecasting Turbulence in Hospitals for a fixed term of 17 months. It is an exciting opportunity to be involved in interdisciplinary research that will underpin innovative solutions for healthcare management.

The Applied Research Collaboration (ARC) Wessex is an organisation funded by the National Institute of Health Research (NIHR) with a remit to support applied health and care research that responds to, and meets, the needs of local populations and local health and care systems. The NIHR ARC Wessex is one of 15 ARCs across England, which aims to improve the health and care of patients and the public within and beyond the Wessex region. 

Our ARC conducts applied health research to improve patient outcomes; quality, delivery and efficiency of health and care services; increase the sustainability of health and care systems through collaborative partnership. We have a close relationship with regional stakeholders, including NHS organisations, universities, charities, local authorities and others.

FORTH aims to understand how demand surges for acute hospitals lead to slower and chaotic patient flow, a phenomenon we call turbulence, which affects the hospital's ability to deliver quality care. We will analyse a large dataset containing Electronic Health Records, aiming to define and understand the causes of turbulence. We will then create models for short-term prediction of turbulence, to help hospitals develop proactive demand management plans.

The successful candidate will to work with the team to achieve the objectives and be responsible for the technical work regarding data analysis and implementation of various models, which will require programming proficiency. For example, you will use artificial intelligence (machine learning) to predict the remainder of a patient's spell at a hospital, given their characteristics and the activities carried out in the current stay. You will also develop models that combine individual patient's predictions and future demand to predict short-term turbulence, with the goal of informing proactive demand management strategies. You will be part of an interdisciplinary team across the Business School, Health Sciences and Engineering who will work and collaborate closely with stakeholders from acute hospitals in the region.

Applications for Research Fellow positions will be considered from candidates who are working towards or nearing completion of a relevant PhD qualification.  The title of Research Fellow will be applied upon successful completion of the PhD.  Prior to the qualification being awarded the title of Senior Research Assistant will be given.

Education and skills required 

- PhD in Operational Research, Mathematics, Statistics, Engineering or Computer Science (or equivalent). 

- Detailed understanding and knowledge of programming languages, ideally C/C++ and Python or R.

- Solid background in machine learning predictive models, including theory and implementation. 

- Working knowledge of stochastic modelling and Markov models.

- Experience with computational implementation of operational research or network optimisation models using appropriate software tools.

Salary and relevant information:

This is a full time post based at Southampton Business School, with salary compatible with a Level 4 Post-Doctoral Research position.

The employing organisation is the University of Southampton, which offers a competitive salary, pension scheme and other benefits.

For an informal discussion about the post, please contact Edilson Arruda, e.f.arruda@southampton.ac.uk.

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