Data Science and Machine Learning Applied to the Discovery of Solid Lithium Ion Conductors

New inorganic materials are needed to advance technologies such as batteries for electric vehicles and grid storage, and to develop basic science. This PhD project is an exciting opportunity for the development and application of methods taken from data science and machine learning to the discovery of new inorganic materials which will function as the electrolyte within an all solid state lithium ion battery. The student will be part of a wider project addressing the Faraday Challenge “Batteries for Britain”, and based in the newly-opened Materials Innovation Factory at the University of Liverpool.

As well as obtaining knowledge and experience in data science, machine learning and inorganic material discovery, the student will develop skills in teamwork and scientific communication as computational and experimental researchers within the team work closely together. Applications are welcomed from candidates with a strong undergraduate interest and/or background in data science, machine learning, computational materials discovery or related fields.

The studentship will be jointly supervised by Dr Matthew S Dyer (Department of Chemistry) and Dr Vitaliy Kurlin (Department of Computer Science).

The successful candidate should have, or expect to have, at least a 2:1 degree or equivalent in Computer Science, Mathematics, Chemistry, Physics or Materials Science. Please apply by completing the online postgraduate research application form. Applications should be made as soon as possible. Informal enquiries should be addressed to Dr Dyer ([Email Address Removed]).

GTA eligibility (EU and non-EU students) - Depending on the successful applicant (EU or non-EU) this studentship would include a commitment to work up to 144 hours per academic year to help with teaching-related activities in modules currently taught in the Department of Chemistry, as assigned by the Head of Department or his representative.