This research project is focused on objects that scatter fields. The field may be electromagnetic, acoustic or elastic. When an incident probing field is launched into a medium that contains an object, that object will disturb the field and scatter it. This disturbance can be detected and one can hope to use the detected signal to identify properties of the scattering object. This project will explore the use of Deep Learning to use these signals to determine the shape of the object.
Applicants will be required to:
- Demonstrate knowledge of elliptic partial differential (e.g. Helmholtz) equations.
- Demonstrate experience in scientific computing (e.g. Matlab, Python, C/C++).
- Configure and use off the shelf software.
Applicants will have or be expected to receive a first or upper-second class honours degree in an Engineering, Computer Science, Design, Mathematics, Physics or similar discipline, and to meet English language requirements. A Postgraduate Masters degree is not required but may be an advantage.
Experience in Scientific Computing, Applied Mathematics and Partial Differential Equations is essential and experience in Python, Machine Learning, Unix and/or GNU/Linux is an advantage. You’ll also need a willingness to embrace a wide variety of both established and emerging areas in applied and computational maths, data science, artificial intelligence and machine learning. In addition, you should be highly motivated, able to work in a team, collaborate with others and have good communication skills.
Your application should address your experience and competencies to date in all of the areas mentioned above.