A Research Fellow is sought to conduct original research within the Health Data Research UK team (based at the Usher Institute, University of Edinburgh) focusing on the development and application natural language processing methods to extend the phenotyping potential of disease status algorithms to additional linked datasets and unstructured data. This will be used to help streamline identification of patients for clinical trials and stratification of patients for disease classification, outcome prediction, patient trajectories across the life-course, adverse drug reactions, and identify drug-repurposing opportunities. The role will be focused on the development and application of natural language processing methods, to extend the phenotyping potential of disease status algorithms to additional linked datasets and unstructured data.

Candidates will have, or be near completion of, a PhD degree or equivalent in computer science, informatics or a related discipline (e.g., artificial intelligence, machine learning, natural language processing). The appointee will have strong programming skills, experience of machine learning techniques to solve real world problems, or of applying data science technologies on large scale datasets.

The post is fixed term, full-time (35 hours per week, however part-time hours would be considered for the right candidate), funding is in place to support the role from April 2020 for 18 months.

Informal enquiries may be directed to Dr Lucy McLoughan, Health Data Programme Manager (lucy.mccloughan@ed.ac.uk)