Research Associate in Epidemiology and Biostatistics

We are seeking a talented post-doctoral researcher with a background in epidemiology, biostatistics or nutrition and expertise in evidence synthesis. You will contribute to systematic evaluations of research evidence in nutritional epidemiology, and participate in the development and evaluation of AI-enhanced techniques and tools to streamline systematic literature review processes.

You will join a research team at the forefront of an established international research collaboration, the Global Cancer Update Programme () of the World Cancer Research Fund International (). CUP Global evaluates evidence on the impact of diet, nutrition, anthropometric characteristics, physical activity, and sedentary behaviour on cancer prevention and prognosis. The programme has yielded numerous publications in leading scientific journals, and its recommendations are used by the public, patient groups, regulatory agencies and policy makers internationally

You will work with a team of epidemiologists, biostatisticians, nutritionists, a software engineer/database manager and a project manager, to conduct systematic literature reviews and meta-analyses on lifestyle factors and cancer risk and prognosis.

In a new WCRF-funded initiative, the Data Automation Project, our team is collaborating with a team of machine learning (ML) experts at the University of Bristol, to design and implement AI-based tools to semi-automate some of the SLR processes in CUP Global.

You will liaise with the team at the University of Bristol leading this project, to integrate the pipeline of ML models within a tailored systematic review platform, to (semi) automate aspects of article screening and inclusion, data extraction and risk of bias assessment. The focus of this work will be on testing and validating the new tools and the AI-enhanced pipeline, evaluating their predictive performance, utility, limitations and advising on improvements.

You will work closely with the other members of the team to conduct the research, prepare scientific reports and publications, and applications to secure external research funding. You will have the opportunity to collaborate with other researchers within ICL, the University of Bristol, at WCRF and with international experts involved in CUP Global.

We are looking to appoint a dedicated post-doctoral researcher with a background in epidemiology, nutrition, biostatistics, health data science or other related disciplines, with excellent analytical and interpretative skills of evidence synthesis data.

In addition, you should have a solid understanding of concepts behind ML techniques, and of methods and classification metrics for evaluating and validating supervised/unsupervised predictive models.