RiSC+ Research Fellow - UK Food Supply Chains

This post is a critical role, and as such, successful applicants will have responsibilities in independent research, research planning and reporting and for collaboration with project partners.

The post is part of the ReImagining Supply Chains Network Plus (RiSC+ Network) project, whose main aim is to model and reimagine supply chains across the UK in food, critical minerals and fashion. The RiSC+ Network will offer evidence that exposes vulnerabilities, remedies current risks and demonstrates future potential, ultimately helping to empower the UK to move towards more resilient and secure supply chains.

About the person:

You will be a highly productive, ambitious and collaborative member of the RISC+ team assisting in the development of research proposals and the planning and delivery of the research activity specifically in Modelling UK Supply Chains as complex systems for resilience.

Essential criteria:

• Hold at least a 2:1 honours degree in Computer Science, Data Analytics, Business Analytics, Operations Research, Industrial Engineering or closely related discipline.
• Have, or be about to obtain, a relevant PhD in Computer Science, Data Analytics, Business Analytics, Operations Research, Industrial Engineering or closely related discipline (candidates about to receive their PhD should provide proof that their viva is scheduled within two months).

Recent relevant research experience to include:

• Demonstrable experience in data analytics, business analytics or big data analytics.
• Demonstrable experience in handling complex, interconnected and highly dimensional data.
• Demonstrable experience with computer coding languages (such as R, Python).
• Demonstrable experience with the use of MATLAB or similar software packages.
• A track record of publications appropriate to stage in career.
• Demonstrable experience in programming/scripting, beyond that taught in undergraduate engineering courses.
• A proven track record of using relevant techniques to carry out analyses, critical evaluations, and interpretations of data as relevant to the research project.
• Working effectively as part of a research team in the development and promotion of the research theme.

To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information document on our website.

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