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Computer Aided Discovery of Organic Materials for Electronics and Bioelectronics

  • Full or part time
  • Application Deadline
    Friday, January 31, 2020
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

One PhD studentship is available to work on the theoretical modelling of materials for electronics applications. The goal of the project is to develop methodology to drive the discovery of new materials in this area based on a combination of computational chemistry methods, physical models and data driven approaches (e.g. machine learning). The project will be supervised by Prof. Alessandro Troisi and it is suitable for students with interest in physical chemistry (e.g. spectroscopy, electrochemistry) or computational chemistry (quantum chemistry or molecular simulations). The project involves substantial work with high performance computing. The methods developed within the project will be applied to the study of one (or more) of the following materials classes: energy storage materials, bioelectronics materials, photocatalytic system.

Further information on the research group can be found at https://sites.google.com/view/troisigroup/home
The project will be based at the Materials Innovation Factory a new institute devoted to innovative approaches to materials discovery (https://www.liverpool.ac.uk/materials-innovation-factory/).

It is recommended to make informal enquires to Prof. Troisi before applying. Please include your CV on your first contact and a brief explanation of your interest in the research area of this studentship.

To apply for this opportunity, please visit: https://www.liverpool.ac.uk/study/postgraduate-research/how-to-apply/

Funding Notes

Tax free stipend for the student is approximately £15,200/year. Eligible candidates must be citizen on UK, EU or China and hold a Master degree by the beginning of the studentship. The applicants must have direct experience with computational or theoretical research, e.g. an undergraduate research project or summer placement. Experience with computer programming and data analysis is desirable but not essential.

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