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New Knowledge and Tools for Topological Characterisation of the CSD Subset of Metal-Organic Frameworks (MOFs)

  • Full or part time
  • Application Deadline
    Friday, August 30, 2019
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

We are currently recruiting an outstanding PhD candidate to start at the Department of Chemical and Biological Engineering at The University of Sheffield in collaboration with the Cambridge Crystallographic Data Centre (CCDC) in Cambridge. The project is partly funded by the CCDC. Non-UK and non-EU applicants who wish to be considered for this project will need to demonstrate that they have the funds to meet the shortfall in fees. The start date for the position is ideally September 2019 to January 2020.

With unparalleled potential to investigate thousands of structures in a short time, computational high-throughput screening (HTS) is extremely well suited to unravel trends in key metal-organic framework’s (MOF) properties, establish structure-property relationships and guide future synthetic efforts. In the last three years, the computational analysis of structures in the CSD MOF subset has been focused on the characterization of geometric (e.g. largest pore size, pore volume, surface area) and gas adsorption properties. Clearly, previous computational work has delivered important insights, but it has not yet fully characterised properties such as the local environment of organic/inorganic clusters and the underlying topology of the identified MOFs in the CSD MOF subset. this PhD studentship focuses on synergetic combination of expertise and disciplines from the CCDC scientists in crystallography, materials science and software development, and the Sheffield team’s know-how in database generation, porous materials characterisation, and molecular-level simulations. Included in this goal is the development of tools to characterise MOFs and predict structure-function relationships to accelerate materials discovery.

This is a multidisciplinary project and the successful candidate will benefit from an extensive peer-group of researchers at the CCDC in Cambridge and The University of Sheffield, as well as acquiring skills at the interface between, materials science, chemistry and big data science, which are in high demand in both industry and academia.

For more information, please contact Dr Peyman Z. Moghadam at The University of Sheffield using .

Funding Notes

The ideal candidate will have a first class degree or equivalent in computer science, chemistry, or chemical/materials engineering, experience in cross-disciplinary work, excellent computer skills and a hands-on approach to problem solving. No prior knowledge of molecular simulations is necessary.

If English is not your first language, then you must have International English Language Testing Service (IELTS) average of 6.5 or above with at least 6.0 in each component.

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