Research Associate in Control-Based Continuation

We seek a highly motivated Research Associate who is interested in working as part of a team at the interface between Engineering and Applied Mathematics to investigate new methods for exploring the nonlinear behaviour of engineered systems and to develop numerical continuation techniques for physical experiments.

Modern test methods for investigating the dynamics of engineered structures are inadequate for dealing with the presence of significant nonlinearity since they have largely been developed under the assumption of linear behaviour. In contrast, control-based continuation (CBC), a versatile non-parametric identification method, has been developed with nonlinearity in mind from the beginning. It has been demonstrated on simple experiments but now advances in underlying methodology are required to apply CBC to real-world experiments which have higher levels of measurement noise and many degrees of freedom. The versatility of CBC is such that, with these advances, it will also become relevant for researchers studying nonlinear systems in both engineering and other fields, such as in the biological sciences.

We are seeking a Research Associate to drive this research forward alongside researchers working on closely related problems from the Departments of Engineering Mathematics, Mechanical Engineering and Aerospace Engineering. Support will be readily available from the investigators David Barton, Simon Neild and Djamel Rezgui. More widely, you will be part of the Dynamics and Control research group and the Applied Nonlinear Mathematics research group both of which carry out cutting-edge research in a wide range of application areas.

CBC presently draws on a wide range of underlying areas including, but not limited to, dynamical systems and bifurcation theory, system identification, control theory and machine learning. Applicants are expected to have experience in at least one of these areas in addition to a first degree and preferably a PhD in Applied Mathematics/Physics/Engineering (or a closely related discipline).

Possible initial avenues of research include
•Improving the robustness of CBC in the presence of noise using surrogate models. Gaussian processes have previously been investigated and may be useful.
•Investigating the scaling up of CBC to many degree-of-freedom systems. Ideas from numerical continuation of PDE systems could yield insights.
•Implementation of CBC on existing aerospace experiments for dynamic testing and wind tunnel testing.

The post is available from 1 June 2017 with funding available for up to three years.

Please direct any questions to David Barton, david.barton@bristol.ac.uk.