Research Associate in Epidemiology and Biostatistics

About the role

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.

What you would be doing

You will join a research team at the forefront of an established international research collaboration, the Global Cancer Update Programme (CUP Global) of the World Cancer Research Fund International (WCRF). 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 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.

What we are looking for

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.

What we can offer you

• The opportunity to join a leading research team at the forefront of systematic evaluations of research evidence in nutritional epidemiology
• Work at the intersection of epidemiology, biostatistics and machine learning, participating in the development of new tools and techniques in this emerging research filed
• Grow your career with tailored training programmes for academic staff including dedicated support with navigating your career and managing research as well as opportunities for promotion and progression.
• Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes).
• Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing.

Further information

This is a Full time Fixed Term contract based at our White City Campus

The post-holder will be accountable to the ICL CUP Global Principal Investigators (PIs):

Dr Doris Chan and Dr Kostas Tsilidis.

For further information or to arrange an informal discussion with the PIs please contact:

Dr Eduardo Seleiro (e.seleiro@imperial.ac.uk).

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