Research Associate in Optimizing Patient Journeys in Healthcare

Job Summary

The Analytics and Operations group at Imperial College Business School is seeking applications for a Research Associate in the area of optimization and machine learning for healthcare. Applicants must hold a PhD in Operations Research, Applied Mathematics or a related field, have strong mathematical skills and a keen interest in healthcare applications.

Based in the Analytics and Operations group, you will conduct research with Prof. Wolfram Wiesemann from that department as well as Prof. Paul Aylin from the School of Public Health. This position aims to apply optimization and machine learning approaches to patient journeys through the healthcare system, with emphasis on improving efficient delivery of high quality and safe care and reducing inequalities. The NIHR Imperial BRC supports research that translates scientific discoveries into new treatments, diagnostics and medical technologies, benefitting patients and communities locally and internationally. Funded by the NIHR, this collaboration between Imperial College Healthcare NHS Trust and Imperial College London provides research infrastructure across both organisations as well as funding specific projects and training schemes.

In the project, you will be using linked healthcare datasets including The Whole Systems Integrated Care (WSIC) linked healthcare dataset in North West London, which is a comprehensive and multi-year dataset that contains information about patients who have received care from multiple healthcare providers within the region. This dataset is particularly valuable for process mining and the optimisation of patient journeys in healthcare because it allows researchers to track the care that patients receive over time and to examine how different types of care may be impacting patient outcomes.

A key purpose of the research will be the identification of bottlenecks and inefficiencies in the healthcare system. By analysing the data contained in the dataset, researchers can identify areas where patients may be experiencing delays or where care may be duplicative or unnecessary. This can be particularly useful for identifying opportunities for process improvement and for developing strategies or algorithms to optimize the flow of patients through the healthcare system. Through this research we hope to gain a deeper understanding of how care is delivered in the region and identify opportunities for improvement that could lead to better patient outcomes and a more efficient healthcare system. We expect the results to be published in top-tier Operations Research journals (such as Management Science and Operations Research) as well as medical journals.

Duties and responsibilities

• You will work as part of an international multidisciplinary research team.
• You will conduct methodological research in optimization and machine learning.
• You will apply the aforementioned research to healthcare, in collaboration with other researchers from the NIHR AI in Health and Care project.

Essential requirements

• PhD in a relevant discipline (e.g. in operations research, applied mathematics, computer science or a related field) and strong mathematical skills. Candidates with a PhD near to completion will also be considered.
• Proven knowledge and skills in operations research, applied mathematics or a related field.
• Proven knowledge, or willingness to acquire knowledge, of process mining in discovering, validating and improving workflows.
• Strong mathematical skills.

Further Information

Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £38,194 - £41,388 per annum.

For further information please contact Wolfram Wiesemann ww@imperial.ac.uk

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