The MRC funded Rule-Based Modelling of Epidemics project aims to bring process calculus to bear on questions surrounding infectious disease modelling. We work primarily with the Kappa process calculus, originally designed for use in molecular biology. It turns out to be very productive in the context of population biology and epidemics and its expressivity is a boon: it allows us to explicitly represent processes that contribute to epidemic trajectories such as behaviour and immune response. Starting from this foundation, this project will establish rule-based modelling as a standard approach in infectious disease modelling.

A Knowledge Exchange Associate (KEA) is a researcher whose primary audience is outwith the academy. Rather than being primarily focused on work in support of research publications, a KEA focuses on getting the new knowledge that they generate out into the world. As a KEA, as part of a wider research group, you will develop the system described above, publish software and designs in the usual way of free and open source software, conduct field tests of the system, as well as objectives and proposals for further development. All of this with guidance from senior colleagues as required. You will conduct individual and/or collaborative knowledge exchange activities, including determining appropriate methods and contributing to the development of new knowledge exchange methods, continually reflecting on practice/methodology.

To be considered for this role, you will have substantial experience software engineering, especially functional approaches and functional programming languages (ideally Ocaml and, though it is not a functional language as such, Julia). Experience with domain specific languages (whether design, implementation or use) is important. Experience with process calculi such as Kappa, BioNetGen, (Bio)PEPA, Bigraphs &c is especially valuable. Experience of standard software engineering practices such as unit and functional testing and the use of revision control systems. Experience with scientific computing and high-performance computing is an asset. A good honours degree and PhD / higher degree or equivalent experience in an appropriate discipline is required. You will have sufficient breadth and depth of knowledge in the relevant fields to contribute to knowledge exchange programmes and to develop knowledge exchange activities. You will have the ability to conduct individual knowledge exchange projects, work directly and independently with clients and user communities, and to prepare new knowledge exchange proposals.