It is now routine in world leading laboratories to perform experiments where single atoms can be placed with atomic precision. These experiments are performed using scanning probe microscopes, and allow us to study the electrical and chemical properties of matter with sub-molecular, and even “sub-atomic” precision.
However, these experiments rely on highly trained expert researchers operating machines by hand in an extremely time-consuming process. There is now significant interest in other fields towards developing machine learning algorithms, and autonomous systems, to allow machines to understand complex problems – for example facial recognition and self-driving vehicles.
In this project the candidate will build on recent developments to develop automation and machine learning algorithms for integration with cutting edge scanning probe microscopes investigating intermolecular and interatomic interactions, essentially teaching a machine to “see” and move single atoms and molecules. This will be accomplished by direct interfacing with the Ultra-high resolution scanning probe microscopes currently housed in the MNP group at the University of Leeds.
The successful candidate for this project should have a keen interest both in experimental physics and in programming (pre-existing experience of Python and/or LabVIEW would be particularly useful) alongside a desire to work as part of a team of dedicated researchers in a challenging experimental environment.
This project is open to self-funded students and is eligible for funding in an open competition across the School of Physics.