Research Assistant / Associate in Stochastic Modelling of Urban Structures
University of Cambridge Department of Engineering
United Kingdom

A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on Stochastic Modelling of Urban Structures. The post holder will be located in West Cambridge, Cambridgeshire, UK. This post presents an opportunity for a research scientist to join a research team based at Cambridge to work on the Stochastic Modelling of Urban Structures as part of the EPSRC funded Programme Grant ICONIC https://iconicmath.org. The research to be undertaken by the postholder will focus on the development of new Bayesian methodologies for inverse problems, including high-dimensional latent Gaussian models, elliptic PDEs and singly-constrained dynamic urban models.

ICONIC aims to develop theory, methodology, and algorithms to propagate uncertainty in mathematical models of socio-economic phenomena in future cities. Funded by a 5-year, £3M EPSRC programme grant, this project is a collaboration between, the University of Cambridge, the University of Oxford, the University of Manchester, and the University of Edinburgh, as well as a number of project partners. ICONIC brings together a research team with the appropriate combination of skills in modeling, numerical analysis, statistics and high performance computing. To give a concrete target for impact, the ICONIC project will focus initially on uncertainty quantification for mathematical models relating to crime, security and resilience in urban environments. Then, acknowledging that urban analytics is a very fast-moving field where new technologies and data sources emerge rapidly, and exploiting the flexibility built into an EPSRC programme grant, we will apply the new tools to related city topics concerning human mobility, transport and infrastructure. In this way, the project will enhance the UK's research capabilities in the fast-moving and globally significant Future Cities field.

Appointment at Research Associate level is dependent on having a PhD or equivalent experience in industry. Those who have submitted but not yet received their PhD will be appointed at Research Assistant level, which will be amended to Research Associate once the PhD has been awarded.

The skills, qualifications and experience required to perform the role are;

The successful candidate will have demonstrable experience in: - data modelling and analysis - experience in developing theoretical analysis of statistical methodology - experience in large scale computing - experience authoring technical documents and scientific papers - proven ability to work in a team - proven ability to communicate effectively

Appointment at Research Associate level is dependent on having a PhD. Those who have submitted but not yet received their PhD will be appointed at Research Assistant level, which will be amended to Research Associate once the PhD has been awarded.

Fixed-term: The funds for this post are available for 12 months in the first instance.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Please ensure that you upload your Curriculum Vitae (CV) and a covering letter in the Upload section of the online application. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application. Please submit your application by midnight on the closing date.

If you have any questions of a technical nature related to the role please email Prof. Mark Girolami mag92@cam.ac.uk and for all other queries concerning the application process, please email Sue Stocks: sms98@eng.cam.ac.uk

Please quote reference NM23762 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.


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