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Machine learning in quantum chemistry - using machine learning to improve the results of quantum chemical calculations

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

Machine learning methods have seen a great deal of recent success in a number of technological fields, and these techniques from applied statistics and computer science are poised to change the fields of computational and theoretical quantum chemistry.

Most current machine learning applications in computational chemistry have focused on inferring results and hence avoiding time consuming density functional theory calculations (for example). This project will take a different approach and use machine learning/artificial intelligence to improve the results of quantum chemical calculations, in terms of accuracy and/or the computational resources required to carry out the calculations.

The project will have both development and application phases, and hence will require some computer programming (possible languges include Python, C++ and Fortran, previous experience desirable but not necessary). Suitable backgrounds include, but not limited to, theoretical/computational chemistry, cheminformatics, computer science, physics, or mathematics.

Further details of the project are available on request.

Funding Notes

This is a self-funded project. The applicant should have or expect to gain at least an upper second class degree, or equivalent overseas qualification, in a relevant subject.

If you have the correct qualifications and access to your own funding, either from your home country or your own finances, your application to work with this supervisor will be considered.

Related Subjects

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