Postdoc Position in Wave Scattering and Propagation in Random Media

Applicants are invited to apply for a postdoc position in applied mathematics at University of Cambridge, UK. The funding allows successful candidates to work for 3 years in the first instance. Potential candidates should apply before December 03, 2018.

A position is available for a Research Associate to work with Prof. I. David Abrahams, NM Rothschild & Sons Professor of Mathematical Sciences and Director of the Isaac Newton Institute, to undertake research on wave scattering and propagation in random particulate materials. The project has two main aims: first to develop mathematical models of ensemble-averaged waves in such materials and second to combine mathematical models with machine learning to improve material characterisation, especially from wave reflection experiments.

The project, which will involve both analytical and numerical methods, will focus on the mathematical modelling of waves in ensemble-averaged materials that contain random distributions of particles, inclusions, or defects. Currently, there is a paucity of analytical approaches that are applicable for a broad range of frequencies and/or for densely packed particles. These are the conditions which lead to significant multiple scattering and occur in a wide variety of applications in engineering and physics. The second aim is to use these mathematical models to generate data for wave reflection experiments covering a wide range of material parameters and frequencies; these data will then be used to train supervised machine learning algorithms. The resulting algorithms should then help answer fundamental questions on characterising random materials.

The ideal candidate must have a PhD in applied mathematics (or equivalent) with a good grasp of both physical and mathematical aspects of continuum modelling. They will have expertise in scalar wave mechanics (i.e. acoustics), vectorial waves and their properties (elastic or electromagnetic), multiple-scattering wave theory and methods in random homogenisation. They should also, ideally, have theoretical knowledge of kernel based regression methods and a proven ability in implementing machine learning methods in Julia/Python. Other desirable skills include asymptotic methods, applied complex analysis, and knowledge of thermal and viscous effects on linear elastic wave propagation.

Applicants should have a strong research track record and may have previous postdoctoral experience. Further duties and their timing are flexible, but include developing and carrying out individual and collaborative research objectives, proposals and projects. Candidates will be expected to plan and manage their own research and administration, with guidance as required. They must be able to communicate material of a technical nature and be able to build internal and external contacts. The post holder may be asked to assist in the supervision of student projects, the development of student research skills, provide instruction or plan/deliver seminars relating to the research area.

Informal enquiries may be directed to Prof. I. David Abrahams (email:

Fixed-term: The funds for this post are available for 3 years in the first instance.


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