Research Assistant
2 weeks ago
The post is funded by the National Institute for Health Research (NIHR) as part of its establishment of number of HPRUs in key priority areas. These research units are collaborations between universities, UKHSA, and other partner organisations and aim to provide centres of excellence in multi-disciplinary health protection research. The HPRU in HCAI & AMR at Imperial College London is a collaboration between Imperial College London, UKHSA, Warwick University, and Cambridge Veterinary School.
Our research theme aims to maximise the utility of data to better understand the underlying causes of antimicrobial resistance (AMR) and develop novel technologies and interventions to minimise this. The projects use linked primary and secondary care data from multiple sources to answer questions around how we can best use linked health datasets to better understand AMR, infection transmission and evaluate policy impact, how the use of advanced methods and tools can enable us to dynamically understand risk and vulnerable populations, and how methodologies can be developed to enhance surveillance of infections and AMR in different healthcare settings.
We are looking for a candidate with strong skills in curating, processing, and analysing large, integrated clinical and non-clinical data to support development of machine-learning (ML) models for clinical decision support, epidemiological trend analysis, outbreak detection, and intervention evaluation. Experience in working with both coded and uncoded data is preferred. Importantly the post-holder will also have a “responsive research capacity role” which will require them to address any approved requests from UKHSA for additional research needed to assist them in fulfilling their role to protect the public and improve the nation’s health. This might include, for example, the investigation of an unexpected surge or outbreak. We encourage candidates from data and / or computer science who want to develop a career in health sector to apply for this role.
Research Duties:
To curate, manage data from multiple sources, including national AMR surveillance hubs and dashboards, published literature; and ensure the validity and reliability of data.To create data processing pipelines for integrated analysis using clinical and non-clinical data around infection and AMR.To characterise risk factors of AMR acquisition in different populations through data analytics such as agent-based modelling, multilevel modelling.To perform predictive analysis using machine-learning based models to detect AMR trends, outbreaks, and intervention outcomes.To assist with the writing of reports and manuscripts, and present findings to colleaguesOther Duties:
To participate in any patient and public engagement involvement and participation activitiesTo undertake any necessary training and/or development.To undertake appropriate administration tasks.To attend relevant meetings.A first / master’s degree (or equivalent) in statistics, data science, or ML / AI, merit and above. (candidates from computer science will be considered if can demonstrate sufficient experience in data analytics).Quantitative data processing and analysis, descriptive and statistical analysisML / AIData formatting and re-structuringWeighting / raking for population samples, imputationAbility to process structured and unstructured / coded and uncoded dataUsing data to support decision-making in public healthData mining from public domain in health-seeking (. websites, social media)Risk prediction and causal inference using MLPredictive modelling for intervention evaluationProficiency in at least one of the following packages: STATA, R, Python
This is a full-time, fixed-term post until 31 March 2025 and you will be based at Hammersmith Campus.
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